Previously at the Festival of Doubt:
This page lists all the talks, discussions, dogmatic rantings, collective sharings, and bunfights, since records began in 2002.2017
When  Topic 

1 Feb  The CarlSIM Spiking neural net simulator : Will Browne 
8 Feb  Anomalies are not outliers : Alex Telfar 
8 Mar  Brainstorming how FoD works : everyone 
22 Feb  Monotone Operators : Bastiaan Kleijn 
22 Feb  A Multiscale Consensus Model for Lowlevel Vision : Todd Zickler 
15 Mar  A bit about tensorflow : Mashall 
22 Mar  The Shattered Gradients Problem (if resnets are the answer, then what is the question?) : David Balduzzi 
29 Mar  Reputation and the origin of money : Marcus 
5 Apr  That kernel trick : Kurt WanDuo Ma 
12 Apr  Tensorflow vs PyTorch : Nico Despres 
19 Apr  Demo for Raspberry Pi : Kurt 
10 May  Mutual information and all that : Steven (drjellyman?) 
17 May  GANs (Generative Adversarial Networks) : Hamed Sadeghi 
24 May  Intro to Variational Inference via Normalising Flows : Mashall 
31 May  I've been thinking about... : Shima and Harry 
7 Jun  Thoughts on ML : David Balduzzi 
14 Jun  Planning session choosing ICML papers to read : everyone 
21 June  "Failures of GradientBased Deep Learning" : allin 
28 June  "Sharp Minima Can Generalize For Deep Nets" : Alex Telfar 
5th July  Variational Boosting https://arxiv.org/abs/1611.06585 : Todd Zickler 
12th July  Deep CORAL: Correlation Alignment for Deep Domain Adaptation https://arxiv.org/abs/1607.01719 : Kurt 
19th July  Recurrent highway networks : Harry Ross 
26th July  Convolutional Sequence to Sequence Learning with Wavenets : Paul Mathews 
2nd Aug  GANs and stuff : Hamed 
9th Aug  ICML on, no FoD 
16th Aug  Paul Rubenstein (student of Carl Rasmussen and 
23rd Aug  ICML hotness : Marcus and Kurt 
30th Aug  RKHS and HSIC : Felix and Kurt 
6th Sept  clash with Prof Martin Butz seminar "From Predictive Sensorimotor Processing to EventOriented Conceptualizations" 
13th Sept  Catchup with everyone who has been away 
27th Sept  "Variational Inference using Implicit Models" https://arxiv.org/pdf/1702.08235.pdf : Mashall 
4th Oct  More on Implicit Models : Mashall 
11th Oct  The symbol grounding problem, with Prof Mark Steedman (Edinburgh) 
18th Oct  "Duality of Graphical models and tensor networks" (Robeva and Seigal) : Alex 
22 Nov  Use of Prior Information for Ultraefficient Imaging: Paul 
2016
When  Topic 

14 Jan  The difficulty of "explaining away" inference in neural nets : Marcus 
21 Jan  Questions about hand tracking using deepish nets : Kurt 
04 Feb  StronglyTyped Recurrent Neural Nets : David Balduzzi 
11 Feb  "Hi Mark", the daftness of precisionrecall curves, what Pareto meant, and so on 
18 Feb  Will had a notion 
3 Mar  A measure of consciousness: David Balduzzi 
10 Mar  Carving nature at the joints : Marcus Frean 
17 Mar  5 minutes each on "Something I learned this week was..." 
31 Mar  Informal discussion 
7 Apr  Tony on Tenenbaum and Freeman's "Separating Style and Content with Bilinear Models" 
14 Apr  Alex on tSNE 
5 May  Michael Radich on modelling author attribution anomalies in the Chinese Buddhist canon 
12 May  "5 minutes of what did I learn this week" 
18 May  JP: Randomised Linear Algreba 
25 May  JP, David, Marcus on various ideas about learning from residuals (ResNets, Gradient Boosting, Upstarts) 
8 June  Alex and Paul : everyone install and get going with tensorflow 
15 June  Eigen means characteristic 
22 June  "5 minutes of what did I learn this week" 
July 6  Disentanglement, and Ideas for pet ML Course 
July 13  David: ICML debrief 
July 20  Elisenda: Emergence of barter 
July 27  Alex: how autograd works 
Aug 3  Marcus: thermal perceptrons 
Aug 10  Around the table, 5 mins on something you're doing 
Aug 17  Tony: RMSProp better in a weird way 
Aug 24  Alex: discuss "Decoupled neural interfaces using synthetic gradients" 
Aug 31  Bastiaan: convex optimization neural network 
Sept 7  Mashall: Gaussian process vs Kalman filter 
Oct 10  Marcus and Tony: disentangling messedup causes 
Nov 16  Matt O’Connor : consensus optimization 
Nov 30  Marcus: autoencoding without an encoder 
2015
When  Topic 

9 April  "Hi David" : David Balduzzi 
16 April  PGMs : Paul Teal 
23 April  What are the options for getting errors bars on predictions? : Mashall Aryan 
30 April  Random Bits Regression : JP Lewis 
14 May  Probabilistic Back Propagation : Mashall Aryan 
21 May  Kingma & Welling's "Variational Autoencoders" : David Balduzzi 
28 May  Alpha matting : William 
4 June  Finding diffuse sources in astronomical images : Tony ButlerYeoman 
11 June  FreeEnergymeetsLCS paper : Will Browne 
18 June  AlexNet : Gif 
17 July  A Topic in machine learning : Mashall Aryan 
24 July  multiplecause RBMs : Marcus 
31 July  Conjugate gradients : JP Lewis, Tony ButlerYeoman, Marcus Frean 
6 August  deConv nets : Gif 
20 August  Saddle points : Marcus Gallagher, UQ 
27 August  Discussion... : Marcus Gallagher, UQ 
3 September  ADMM : Arian Miralavi 
10 September  Reservoir Computing : Leo Browning 
24 September  discussion of a draft paper (Semantics, Representations and Grammars for Deep Learning) : David Balduzzi 
1 October  Consciousness, strong AI, functionalism : Marcus Frean 
8 October  CMAES works, but how? : Will Browne 
15 October  Decamped to the consciousness seminar over in Philosophy 
22 October  More about the details of CMAES : Will Browne 
29 October  No meetup this week  too many people away 
17 November  Social install / play with TensorFlow 
26 November  Discussion of fast Gaussian process inference 
3 December  Further discussion of Gaussian processes 
10 December  Discussion of Lagrange multipliers, generalisations etc : Bastiaan 
2014
30 July  Learning hinges : David 
7 Aug  How to explain Gaussian processes : JP 
14 Aug  Falsification : David 
21 Aug  Deep planning : Marcus 
4 Sept  Pulling faces : JP 
2013
When  Topic 

25 Feb  The problem of induction: Hume, Popper, and OckhamviaBayes 
8 March  Deep learning 
22 March  The Blue Brain project : Praveen 
5 April  informal discussion of a Topic of Interest 
19 April  The prospects for detecting characteristic virus "crystals" in electron micrographs: Marcus 
26 April  I can't remember the topic. Was it MML? 
10 May  Farewell for Anna Friedlander 
17 May  Mona: practice talk for her phd proposal seminar 
6 Aug  Science of music 
13 Aug  ASMR + anticipated perception 
20 Aug  16000 cores for 3 days on 200 million random YouTube images... deep learning of "face cell" etc  reportage here 
27 Aug  Time rotation and free will 
3 Sept  Participation in the Visualising Correspondence Networks "hackfest" for digital history, run by Sydney Shep 
10 Sept  Uniqueness and Legacy 
1 Oct  Discussion of a Topic of Interest 
8 Oct  Praveen: fast sparse particle filtering 
15 Oct  Incentivizing good governance 
2012
When  Topic 

10 Dec  Marcus: Stag hunting 
3 Dec  Mona and Praveen: RVM and SVM 
19 Nov  Anna: strategies for binning pixel intensities in radio astronomy images 
5 Nov  Marcus and Praveen: an idea for multitarget tracking 
29 Oct  Mona: sparsity and the Relevance Vector Machine 
8 Oct  More on Functionalism vs Dualism 
24 Sep  Discussion: Functionalist theories of mind 
10 Sep  Discussion of Sophie Deneve's ideas (mf) 
3 Sept  Around the table: Praveen's weighted clustering idea, Mona's relevence vector machine issue, Anna's scoring of bounding boxes 
27 Aug  How to prepare the (PhD) proposal document 
20 Aug  More on reinforcement learning (mf) 
13 Aug  Introduction to reinforcement learning (mf) 
6 Aug  Discussion: what is unsupervised learning, really? 
30 July  Anna: introduction to topic models / latent Dirichlet allocation (LDA) 
23 July  "What is the most challenging part of machine learning?" 
16 July  Bhakta: "no brainstorming please!". A general discussion of Gaussian processes (different views of). 
9 July  Discussion: a potentially good fit for Gaussian processes and active vision 
25 June  brainstorm the general problem of visual "attention" with everyone 
18 June  Discussion (A+M) of strategies for setting bins in histograms of image pixel intensity 
11 June  More about the Jeffreys prior  we went over the "bent coin" example 
30 May  priors: improper, conjugate, and uninformative. (The Jeffrey's prior and the apparent rationality of negative pseudocounts...) 
23 May  We mainly talked about Haar wavelets and ToktamEbadi's Problem: using them to classify digits of unknown rotations 
16 May  Why do we max likelihood of parameters in a Gaussian Process? 
9 May  PGM stuff  we talked about supervised/unsupervised learning and how that was reflected in the graph. Discussed but didn't resolve why 'features' should be independent if possible  surely there's a PGM perspective on that? 
2 May  Discussion around Daphne Koller's PGM course, which we're all sitting in on 
25 April  "the thing you're most confused about in ML, this week"... I think we ended up talking about Anna's images and the issues with detecting smudges in them 
18 April  Second meetup: let's all take the PGM course at http:www.coursera.org 
5 April  First meetup: coffee, introductions 
2010
When  Who  Topic 

18 Feb  Keith Cassell  Ask Peter Norvig Anything (without Peter Norvig). Conducted under Keith's Rules of Disorder 
2009
26 Nov 2009  Peter Andreae  Vietnamese Document Representation and Classification (practice talk for AI09) 
12 Nov 2009  Miles Thompson  Understanding money on the social network 
1 Oct 2009  Peter Andreae  Learning to act in a complex world 
6 Aug 2009  Sergio Hernandez  How to predict the past using future imprecise information 
14 May 2009  Mengjie Zhang  There Is a Free Lunch for HyperHeuristics, Genetic Programming and Computer Scientists 
30 Apr 2009  Marcus Frean  Restricted Boltzmann Machine II 
16 Apr 2009  Daniel Crabtree  Restricted Boltzmann Machine 
2 Apr 2009  Will Smart  A mathematical model for visual beauty 
19 Mar 2009  Richard Proctor  Using information theory to improve music theory 
12 Feb 2009  Social Evolution Reading Group  Casual discussion 
5 Feb 2009  Marcus Frean  Solving expensive parameter optimization problems, without going broke 
29 Jan 2009  Adam Clarke  Exploring the space between lowlevel sensory inputs and highlevel concepts 
22 Jan 2009  Social Evolution Reading Group  Sexual selection and Fisher's runaway process 
15 Jan 2009  Keith Cassell  Applying the concepts of social network analysis to software engineering 
8 Jan 2009  Social Evolution Reading Group  Price's equation applied to Group Selection 
2008
When  Who  Topic 

18 Dec 2008  Kourosh Neshatian  In Search of Intelligent Aliens: On Scalability of Intelligence 
11 Dec 2008  Social Evolution Reading Group  animal communication and honest signaling 
4 Dec 2008  no discussion  nb. most staff away at AI'08 
27 Nov 2008  Will Smart  Will's neat idea for a robot  Mechanical worms and snakes 
20 Nov 2008  Tudos Gentes  We talked about honest signals, and Fisher's runaway process 
13 Nov 2008  Social Evolution Reading Group  altruism and inclusive fitness 
6 Nov 2008  Dirk Derom  METANEVA  a tool for neuroinformatics 
30 Oct 2008  Social Evolution Reading Group  basics of modeling evolution as variation + selection, basics of games 
23 Oct 2008  Maciej Wojnar  Artificial Intelligence vs Artificial Minds, discussion of the Technological Singularity 
15 OCt 2008  Keen Persons  Meeting to talk about FoD Reanimated 
2 May 2008  Sergio Hernandez  The Populationbased particle filter 
5 Feb 2008  Rene Doursat  Architectures That Are SelfOrganized and Complex: From Morphogenesis to Engineering 
2007
When  Who  Topic  Abstract 

29 Oct 2007  Daniel Crabtree  Understanding Query Aspects with applications to Interactive Query Expansion  This is a practice talk for a paper that I am presenting at WI 2007 in Fremont, California in a few days time. The abstract of the paper follows. For many hard queries, users spend a lot of time refining their queries to find relevant documents. Many methods help by suggesting refinements, but it is hard for users to choose the best refinement, as the best refinements are often quite obscure. This paper presents Qasp, an approach that overcomes the limitations of other refinement approaches by using query aspects to find different refinements of ambiguous queries. Qasp clusters the refinements so that descriptive refinements occur together with more obscure and potentially better performing refinements, thereby explaining the effect of refinements to the user. Experiments are presented that show Qasp significantly increases the precision of hard queries. The experiments also show that Qasp’s clustering method does find meaningful groups of refinements that help users choose good refinements, which would otherwise be overlooked. 
28 Sep 2007  Sergio Hernandez  PhD Seminar practice talk  Sensor fusion problems occur when multiple sensors are capturing information from an observed environment. Multiple sensors can provide more accurate estimates than their single counterpart, but it is hard to combine the whole information to form a single estimate. The measurements usually have some level of internal noise as well as environmental uncertainty. Combining all the information gathered so far is a challenging computational problem, that can be even more difficult when the environment is nonstationary and the model dimension is also unknown. This PhD thesis will develop a Bayesian method for calculating the probability of the current state of a system from noisy observations, when the dimensionality of the model is changing. The method proposed uses point process theory for the timevarying number of observations and sequential Monte Carlo methods for estimating the system state. 
27 Jul 2007  Daniel Crabtree  Exploiting Underrepresented Query Aspects for Automatic Query Expansion  This is a practice talk for a paper that I am presenting at KDD 2007 in San Jose in early August. The abstract of the paper follows. Users attempt to express their search goals through web search queries. When a search goal has multiple components or aspects, documents that represent all the aspects are likely to be more relevant than those that only represent some aspects. Current web search engines often produce result sets whose top ranking documents represent only a subset of the query aspects. By expanding the query using the right keywords, the search engine can find documents that represent more query aspects and performance improves. This paper describes AbraQ, an approach for automatically finding the right keywords to expand the query. AbraQ identifies the aspects in the query, identifies which aspects are underrepresented in the result set of the original query, and finally, for any particularly underrepresented aspect, identifies keywords that would enhance that aspect’s representation and automatically expands the query using the best one. The paper presents experiments that show AbraQ significantly increases the precision of hard queries, whereas traditional automatic query expansion techniques have not improved precision. AbraQ also compared favourably against a range of interactive query expansion techniques that require user involvement including clustering, weblog analysis, relevance feedback, and pseudo relevance feedback. 
22 Jun 2007  Jason Xie  Practice Talk for GECCO 2007  Talk 1: An Analysis of Constructive Crossover and Selection Pressure in Genetic Programming Talk 2: Another Investigation on Tournament Selection: modelling and visualisation 
15 May 2007  Daniel Crabtree  QC4  A Clustering Evaluation Method  This is my practice talk for PAKDD 2007 where I will be presenting this paper next week. Its about evaluating clustering algorithms. Practically nothing about web page's or web search in this talk. But obviously there are some web examples thrown in there for good measure and of course the ubiquitous Jaguar example you are probably all too familiar with by now. 
2006
When  Who  Topic  Abstract 

7 Dec 2006  Daniel Crabtree  Query Directed Web Page Clustering  A practice talk for the paper "Query Directed Web Page Clustering", which is a paper that I am presenting at Web Intelligence 2006 in Hong Kong at Christmas. It's an interesting clustering algorithm that gets very good performance. The presentation is to be 20 minutes long. 
17 Nov 2006  Yun  A generic model of knowledge transfer, incremental machine learning, and recommender systems  The practice of my Phd proposal talk. 
13 Oct 2006  Sergio Hernandez  Discussion of "Bayesianoptimal design via interacting particle systems".  I've found this very interesting paper that I think it's the future of computing 
4 Aug 2006  Marcus Frean  Formation and recovery of topographic mappings in the brain  I will describe a model for the formation of topographic mappings in the brain that incorporates Ephephrin signalling and is able to account for earlier experiments involving expansion and contraction of the map following surgical interventions. Robustness of the map is achieved by invoking (a) regulation of ephrin expression in tectal cells that are innervated from the retina, and (b) smoothing of ephrin levels in the tectum via a local diffusion process. 
30 Jun 2006  Huayang Xie  Practice Talk for CEC2006: gpGP: good predecessors in Genetic Programming  
9 Jun 2006  Marcus Frean  Discussion on particle filtering  Discussion around the superbasics of particle filtering, as I understand it  see readings/PFmorons.pdf . 
26 May 2006  Sergio Hernandez  Where does the mind stop and the rest of the world begin?  It is well known that bayesian methods are not so straightforward in the pattern recognition framework. For this reason, lots of different techniques has arised in order to solve the untractability and the parameter estimation in sequential learning for general state space models. This talk will define some approaches and hopefully will explore new research directions for this problem. 
19 May 2006  Gareth Baxter  How to win friends and influence people: the dynamics of language change.  An introduction to the Language Change modelling I did for my PhD, and am attempting to continue... 
5 May 2006  Will Smart  Unifying dynamic sequences (fragments) and mechanical analogies (in genetic programming).  Mock for the PhD proposal seminar I will give to a slightly less critical audience on the 11th at 11. This will be of interest to anyone who either wishes to see how the great dream of the GP building block hypothesis may finally be seen in all its awesome glory, or wishes to find out how it may be shown that it fails where one may expect it to hold firm. Also those who enjoy GP, schema theory, fragments, the origami of absurdly complex algorithms, or picking holes in hardearned research may be interested. I will talk on fragments in GP; a fragment is a connected subgraph of a program tree. I plan to explore how fragments, as schemas, propagate through evolution in the remainder of the PhD. Using tools I am developing, fragments in populations and evolutions of GP will be identified. Analysis of the fragments will lead to greater knowledge of the accuracies of the GP building block hypothesis and GP schema theory. It is also predicted that intelligent use of fragments will also lead to better GP. 
7 Apr 2006  Cam Skinner  Mutation, Schmutation.  Mutation shown to be harmful: random search is better than mutation in GA's 
31 Mar 2006  Jason Xie  Practice Talk for EuroGP: population clustering and GP for stress detection.  
24 Mar 2006  Cam Skinner  Informal presentation on Mutation in GAs  Why random search is better than mutation in GA's Followed by a flame session led by Maciek, if Cam runs out before 4.45pm 
2 Mar 2006  Daniel Crabtree  Improving Web Page Clustering with Global Document Analysis  This is just a short talk (15 minutes), it is going to be a practice for a talk I am giving at a Workshop in Auckland on Saturday. I would like to have comments on the talk and get any last minute ideas for improving it. After the talk, I can discuss the work further and elaborate on anything that interests anyone or if noone is interested, it'll be a very short FoD. Here is the abstract for the talk: Web page clustering methods categorize and organize search results into semantically meaningful clusters that assist users with search refinement. Finding clusters that are semantically meaningful to users is difficult. In this presentation, I describe a new web page clustering algorithm that chooses clusters that more closely relate to the user's query. The algorithm uses term cooccurence statistics to construct feasible clusters, which are merged, ranked, and selected using an heuristic model of web page clustering usability. The performance of the new algorithm is evaluated and compared against other algorithms and a significant performance improvement is achieved over the other clustering algorithms. 
24 Feb 2006  Maciej Wojnar  Practice run for PhD proposal seminar  I'm doing a practice talk for my PhD proposal seminar. My PhD is about developing an intelligent agent that is effective in the human domain. Specifically, it is about learning effective Goal Decomposition rules. 
2005
When  Who  Topic  Abstract  

18 Nov 2005  Phillip Boyle  Bayesian Model Comparison  Calculating the Evidence  Overview on the use of probabilistic evidence to select between alternate models or hypotheses. On paper this is clear cut, but the hard part is computing the evidence, which amounts to numerical integration. I'll look a annealed importance sampling, which is a method that can do this without having to free up 75 years of computer time.  
4 Nov 2005  Will Smart  Empirical Schema Theory Validation by Finding Common Program Substructures  The topic will be some things I have been doing for my PhD, dealing with repeated code in Genetic Programming (GP). I have been empirically finding common "fragments" of programs, and the talk will be on: * Some previous related material, including schema theory in GAs, GP; * What are fragments in GP programs? * How do we find fragments? * Some things we can do with fragments. Time permitting, I will be describing the problem domain I have recently been using: Object Trackers/Detectors/Classifiers.  
28 Oct 2005  Maciej Wojnar  The Flight of Icarus  Earlier this year, I had several important ideas about agents that act in interesting worlds. In this talk, I'm going to talk about Icarus, a system from 5 years ago that stole my ideas and messed them up. I'll talk about the challenges of creating an agent that can act intelligently, the problems that planning and reacting agents have, and teleoreactive agents that try to avoid these problems by integrating planning and reacting. I'll then describe Icarus, an implementation of a teleoreactive agent, and discuss its limitations and the extensions it requires.  
28 Oct 2005  Mike Paulin (Otago)  The Neural Particle Filter: A model of neural computations for dynamical state estimation in the brain  Recent experimental work in collaboration with Larry Hoffman at UCLA has shown that, as a consequence of fractional order dynamical characteristics of vestibular sensory transduction mechanisms, single spikes generated by vestibular motionsensing neurons can be regarded as measurements of the dynamical state of the head. We hypothesize that this measurement is translated into an explicit Monte Carlo representation in the brainstem vestibular nucleus, which forms a central map of head state. In this representation, neural spikes are regarded as particles and their spatial distribution over the map at any instant represents the brain's knowledge of head state. Particles are constrained to move along axons, corresponding to predefined state trajectories. A network can be constructed so that the distribution of spikes in the map approximates the Bayesian posterior distribution of states given the sense data. The neural particle filter model generates the circuit topology and response properties of real neurons in the brain, from purely statistical principles. See Mike's recent paper for the details.  
21 Oct 2005  Daniel Crabtree  A new approach to sandwiches.  My report on the WI/IAT 2005 international conference. This talk is going to be a summary and overview of interesting ideas, projects, and papers that I can remember about from at the conference. Additional ideas from people that I talked to are likely to be included. This talk is likely to be exceptionally light on technical details  very much in contrast to most of the actual talks at the conference. BTW: I have chosen to keep the automagically generated title.  
14 Oct 2005  Zbigniew Michalewicz (Adelaide)  Open discussion  This follows Zbyszek's seminar to the School earlier in the day. Prof Michalewicz is one of the big names in the area of evolutionary computing (together with John Holland, David Fogel, John Koza, etc.). He has chaired a large number of international conferences in AI, particularly evolutionary computing. He is the author of over 200 research publications, including some famous books, such as "Genetic algorithms + Data Structures = Evolutionary Programs" and "How to Solve It: Modern Heuristics".  
7 Oct 2005  Mengjie Zhang  New kinds of negative social processes (autogenerated).  I am going to discuss some issues in genetic programing, linked to classification and evolutionary computing.  
30 Sep 2005  Marcus Frean  On the optimisation of passive strategies using integration (autogenerated).  I'm going to attempt to draw an analogy between predictive coding and topographic mappings. Your job will be to decide if this profound insight is (a) entirely spurious, or (b) merely a waste of time. The talk will be a boundary case on the "preparedness" dimension.  
23 Sep 2005  Phillip Boyle  100 attempts to find 8 numbers that balance 2 poles  Introduction to and demonstration of an efficient method to find controllers that balance two poles on a cart. The algorithm infers a fitness surface over controller space and uses that to guide its search. I offer an apology in advance to those with a pathological dislike of MATLAB and the 92% of you who don't want to hear the word "Gaussian" more than once per hour.  
16 Sep 2005  Russell Tod  Discussion of distributed phase codes.  
2 Sep 2005  Daniel Crabtree  Web Clustering  New Scoring and Selection Methods, New Evaluation Method  I will give: a 20 minute presentation on a new scoring method and a new cluster selection method. a 10 minute presentation on a new evaluation method. These are two talks that I will be giving at the Web Intelligence Conference in a week or so. So these will be practice runs. Please ask questions and help me sort out any problems with these talks.  
26 Aug 2005  David MacKay (Cambridge)  Distributed Phase Codes for Associative Memory, Prediction, and Latent Variable Discovery  A distributed phase code represents objects by the times of neuronal action potentials in a large number of neurons. If the object has instantiation parameters (for example, scale and pose, in the case of visual objects), the timings and probabilities of the action potentials are smoothlyvarying functions of those parameters. If multiple objects are present, their associated action potential patterns are simply superposed in the distributed phase code. We present simple learning rules that allow distributed phase codes to instantiate associative memory and prediction. The resulting system can store and recall continuousvalued memories, singly or concurrently. Point attractors, line attractors, and manifold attractors are all learned by the same rules. Similar recursive learning rules take distributed phase codes for elementary objects and produce distributed phase codes for higherorder objects. Short Bio: David MacKay is a Professor in the Department of Physics at Cambridge University. He obtained his PhD in Computation and Neural Systems at the California Institute of Technology. His interests include machine learning, reliable computation with unreliable hardware, the design and decoding of error correcting codes, and the creation of informationefficient humancomputer interfaces. 

19 Aug 2005  Yun Zhang  Polly  A soft polynomial network based learning system.  
12 Aug 2005  Richard Mansfield  Rockpaperscissors  A model for the emergence of intransitive competition in biology  
5 Aug 2005  Xiaoying Sharon Gao  learning patterns for information extraction from web pages  I will briefly introduce the projects I am currently supervising and then talk about some recent research on learning patterns for information extraction from Web pages.  
29 Jul 2005  Daniel Crabtree  Web Clustering  A Sneak Peak  I will give a sneak peak into the content of two papers that I've had accepted at the Web Intelligence conference. The full presentation of these with slides will come in a few weeks. This sneak peak is just to introduce some of the interesting ideas in both papers, so I have a feeling for the type of content to include in my actual presentation. I will follow that with some sort of demonstration of my clustering system. I'm pretty sceptical as to whether a live demonstration of any new searches can be done due to time constraints, but there are a few prepared searches to look through. At the start of the talk we will decide on a 1 word search and try to have it ready to view by the end of the talk, so bring ideas for that.  
22 Jul 2005  Maciej Wojnar  Exploiting Structure when Generalizing  I'm going to talk about a couple of "not fully baked" ideas I've had. I'm most interested in trying to achieve the goal of developing an autonomous, intelligent agent that can act effectively in the human domain. In the talk I'll define what I mean by that and explain why I am pessimistic about current methods leading to this goal. The world is a very structured domain and I believe that any algorithm for generalizing that scales to this domain will need to exploit that structure. To keep the talk grounded and not too fluffy I'll talk about some AI systems that exploit structure: a little program I wrote for solving Rubik's cube (fun to watch) and a less trivial program that can make a cup of coffee efficiently in a complex, relational, partiallyobservable world (not as fun to watch). I'll talk about SOAR (a system that unfortunately is very similar to my one), chunking, explanation based learning, and why I think they are dodging the real issue. I'll also talk about (if I have time) David Andreae's PhD thesis program that exploits structure to generalize images. The talk is going to be informal.  
8 Jul 2005  Will Smart  Science using art created with science  In GP we use genetic programs, but what do they look like? In this talk I will demonstrate a realtime raytracing renderer for programs that I have made. The output is stunning, who would have known the wacky shapes (in feature space) that GP uses all the time? Aside from looks, the renderer has things to say about the way GP works, such as the role of functions in GP and causes of early convergence.  
1 Jul 2005  Phillip Boyle  Linear combinations of random features  This is a follow up to the talk Marcus gave on the liquid state machine. I'll be looking at the advantages of learning a linear combination of random features, instead of learning the features themselves. (Here, a feature is just a nonlinear transformation of input space). Advantages include convexity (no local minima) and analytic solutions (no MCMC or nonliear optimisation required). Disadvantages (damn it) will be flippantly glossed over, and then seriously alluded to, and finally embraced in their entirety.  
30 Jun 2005  Huayang Xie  Practice Talk for CEC2006  gpGP: good predecessors in Genetic Programming  
24 Jun 2005  Marcus Frean  factor graphs, probability propagation, and all that.  A dry run of a talk I'll be giving next week in Wanaka at the Hidden Markov Models workshop. Here is the draft presentation as a PDF  
17 Jun 2005  Marcus Frean  In praise of senseless arbitrary complexity.  Last week Mukhlis's talk generated an interesting discussion that I propose we continue, because it's a subject that seems to come up over and over again. I'd like to kick things off by defending (apparently) senseless arbitrary complexity. I'll mention Neal's result relating Bayesian NNs to Gaussian processes, then SVMs, followed by a brief description of a spiking neural model due to Maass et al. The paper I'm discussing is available as #148 from Wolfgang's website (it's in press at J. of Physiology). But I'd really like to see someone (else) tackle #165 sometime soon. Any takers?  
10 Jun 2005  Mukhlis  Review of a paper by Chen and Chen  We reviewed "Toward an evolvable neuromolecular hardware: a hardware design for a multilevel artificial brain with digital circuits", JongChen Chen and RueyDong Chen, Neurocomputing 42 (2002) 934.  
3 Jun 2005  Yun Zhang  Poly & prior schema.  The talk will present a couple of ideas in my Masters (on inductive logic programming)  Polly and Prior Schema. Polly is for reducing the complexity from exponential to polynomial. Prior is to do with our sort of training examples. They turn out to depend on each other so I will present them both. Specifically they have 100% to do with probabilities, 10% with information theory, 50% with neural networks, 10% with belief nets, 30% with logics, 20% with philosophy, and 5% with version space (some normalisation is required).  
27 May 2005  Russell Tod  Spiking neuron models for control.  The talk will present results from my honours project, which investigates realistic models for biological neurons by embedding them in simulated physical agents. These agents attempt to control simple dynamical systems well  for example balancing poles, avoiding obstacles, and the pursuit and evasion of other agents. Their performance on these tasks highlights certain aspects of these realistic neurons compared to the usual "neurons" found in neural nets.  
6 May 2005  Ryan Woodard  Memory.  Is memory the same process in plasmas, SOC models and brains?  
29 Apr 2005  Marcus Frean  GAs to go (can I get fries with that?)  This talk will outline A Topic in Computer Science, or similar. Pondy has agreed to provide interjections. (in fact it was about density modelling using flowfield information from a camera mounted on a car...)  
22 Apr 2005  Chris Brookes (SES)  Lost in space: 7 reasons why geography is hard.  "Nearly everything happens somewhere, and where it happens matters". People understand this intuitively in everyday life but increasingly, with the support of computers and information systems, people are applying geography to make major decisions about managing the world we live in. So geography is important. Unfortunately it is also hard. In this seminar I will introduce some fundamental geographic problems, show why they are hard, and talk about some of the attempts to tackle them using computation. Geocomputation is a relatively new field that has developed from a fusion of Geographical Information Systems and computational methods, and makes significant use of novel techniques such as cellular automata, genetic algorithms, neural networks and multiagent simulations. Anyone with an interest in spatial questions or any computer scientist looking for a real application is welcome to join the discussion.  
15 Apr 2005  Phillip Boyle  Which way is up?  What's the best way to estimate the gradient of a noisy function? Among other things, we might want to do this to help solve stochastic optimisation problems. Simple methods use finite differences. Other methods find interpolating models, and then differentiate the model. The method I have here fits a Gaussian Process model around the point at which you want the gradient. Fortunately, the derivative of a Gaussian Process is itself a Gaussian Process  and this has some helpful consequences. I'll give some examples of this, and try to explain how it works.  
8 Apr 2005  Daniel Crabtree  The problems of searching the web, web clustering, and possible solutions.  This will be an informal talk about the problems that exist with search the web, the capabilities of web clustering and how far it currently goes in addresses the problems of searching the web, and my possible solutions for how the remaining problems could be solved. The talk will start with a brief look at the big picture and the ultimate goal of search and more specifically the ultimate way of obtaining information.  
1 Apr 2005  Maciej Wojnar  Planning as Communication.  I'm going to talk about a paper I read that presents an interesting approach to planning.  
23 Mar 2005  Will Smart  Communal Binary Decomposition for Multiclass object classification.  A trial run of his EuroGP presentation. 