Announcement

We will meet from 12:00 to 1:50 pm every Monday, and will not meet on Wednesdays, starting January 26th.

	Date	Papers	Presenters	Due
Week 1	Jan 21	Overview
Week 2	Jan 26	A Local Neural Classifier for the Recognition of EEG Patterns Associated to Mental Tasks, by Millan, et al. A brain-actuated wheelchair: Asynchronous and non-invasive Brain–computer interfaces for continuous control of robots, by Galan, et al.
Week 3	Feb 2	Non-Invasive Brain-Machine Interaction, by Millan, et al. Error-Related EEG Potentials Generated During Simulated Brain-Computer Intaraction, Ferrez and Millan
Week 4	Feb 9	Class canceled. Please attend Jose Millan's talks at 11:00 and 2:00, room 130 in Computer Science Building.
Week 5	Feb 16	Benchmarks for Basic Scheduling Problems by E. Taillard A Fast Tabu Search Algorithm for the Permutation Flow-Shop Problem by Nowicki and Smutnicki	Shant
Week 6	Feb 23	Project Status Reports.	Everyone. Aim for 10 minutes each.	Only a presentation. No written report. Please turn in a paper copy of your slides in class.
Week 7	March 2	Restricted gradient-descent algorithm for value-function approximation in reinforcement learning by Andre Barreto and C. Anderson Q-Learning with Hidden-Unit Restarting by C. Anderson, Advances in Neural Information Processing Systems, 5, pp. 81--88.	Chuck
Week 8	March 9	3D HAND TRACKING BY RAPID STOCHASTIC GRADIENT DESCENT USING A SKINNING MODEL, by M. Bray, E. Koller-Meier, P. Muller, L. Van Gool and N.N. Schraudolph, Visual Media Production, 2004. (CVMP). 1st European Conference on Publication Date: 15-16 March 2004, page(s): 59- 68. Will go over these slides Increased Rates of Convergence through Learning Rate Adaptation, by Jacobs, Neural Networks, vol 1, pp 295-307, 1988. Improving the Convergence of the Backpropagation Algorithm Using Learning Rate Adaptation Methods, by Magoulas, Vrahatis, and Androulakis, Neural Computation, 11, 1769-1796, 1999. (reading this one is optional) Improving the Convergence of the Backpropagation Algorithm Using Local Adaptive Techniques, Z. Zainuddin, N. Mahat, and Y. Abu Hassan, PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY VOLUME 1 JANUARY 2005	Chuck
	March 16	Spring Break
Week 9	March 23	Large Scale Online Learning, by Bottau and LeCun (only turn in questions for this one). We will review some of these slides. Efficient Backprop, by LeCun, Bottau, Orr, and Muller (section 7.2 helps explain the online kalman algorithm in the previous paper)	Chuck
Week 10	March 30	Project Status Reports		Turn in a two to three page draft outline of your project report. Also use several slides to show results so far, resources used, lines of code, pretty pictures, what is frustrating you currently, remaining milestones.
Week 11	April 6	A Logic for Uncertain Probabilities, by A. Josang Pegasos: Primal Estimated sub-GrAdient SOlver for SVM, by S. Shalev-Schwarts, Y. Singer, and N. Srebro	Steve and Mike
Week 12	April 13	Canceled
Week 13	April 20	Imaging Brain Dynamics Using Independent Component Analysis Face Recognition: A Convolutional Neural Network Approach	Malai and Mark
Week 14	April 27	Isolated word recognition with the Liquid State Machine: a case study read this one, but consult next one if you have time A Model for Real-Time Computation in Generic Neural Microcircuits Modeling multiple autonomous robot behaviors and behavior switching with a single Reservoir Computing Network	Kate and Alex
Week 15	May 4	A Learning Algorithm for Continually Running Fully Recurrent Neural Networks by R. Williams and D. Zipser	Elliott	Complete drafts of all reports due on Friday, May 8th, by 4:00 PM. You may e-mail me pdf files.
Finals Week	May 11, 12:00 - 2:00	4 project presentations	Malai, Kate, Mike, Elliott
Finals Week, 1:30 - 3:30	May 14	4 project presentations	Shant, Steve, Alex, Mark	All final written reports due at noon today.

Schedule Last Semester (CS640)

	Date	Papers	Presenters	Due
	August 27	Identifying natural images from human brain activity, by Kay et al.; Slides from A Neuroanatomy Primer; What we can do and what we cannot do with fMRI, by Logothetis	Chuck (with help from Erik)
Week 1	August 25	Overview
Week 2	Sept 3	Search Space Features Underlying the Performance of Stochastic Local Search Algorithms for MAX-SAT, by Hoos, Smyth, and Stutzle, 2004 Rapid evaluation and evolution of neural models using graphics card hardware, by Clayton et al. Accelerating Brain Circuit Simulations of Object Recognition with a Sony PlayStation 3, by Felch, et al.	Shant and Crystal	Critiques of just the first 2 papers, due in class. Each critique should be at least two paragraphs of summary and critique, followed by several questions you would like to discuss. (Grading for this one will be very forgiving, since this is such a last minute notice.)
Week 3	Sept 10	Achieving organic compositionality through self-organization: Reviews on brain-inspired robotics experiments, by Tani, et al. Sparse Deep Belief Net Model for Visual Area V2, by Lee, et al.	Kate and Stephen	Critiques due in class.
Week 4	Sept 17	Gene selection from microarray data for cancer classification—a machine learning approach, by Wang et al. "Thinking about Not-Thinking”: Neural Correlates of Conceptual Processing during Zen Meditation, by Pagnoni, et al.	Malai and Shant
Week 5	Sept 24	Introduction to reinforcement learning Structured Prediction with Reinforcement Learning, by Maes et al.	Chuck and Mike
Week 6	Oct 1	Learning the Solution to a Puzzle (Chapter 7 primarily), by Chuck, 1986 Midbrain Dopamine Neurons Encode a Quantitative Reward Prediction Error Signal, by Bayer and Glimcher. The paper, Imaging Valuation Models in Human Choice, by Read Montague, et al., will be used by Erik to provide some background. Your critique should be of the Bayer paper, though.	Chuck and Erik
Week 7	Oct 8	Motif Discoveries in Unaligned Molecular Sequences Using Self-Organizing Neural Networks, by Liu et al. Alopex: A Correlation-Based Learning Algorithm for Feedforward and Recurrent Neural Networks by Unnikrishnan and Venugopal	Mark and Elliott
Week 8	Oct 15	Class Canceled. Chuck out of town.
Week 9	Oct 22	Testing, Evaluation and Performance of Optimization and Learning Systems, D. Whitley, et al. Adaptive nonlinear system identification with echo state networks, by H. Jaeger. Also see Echo State Network on Scholarpedia (but you don't have to critique the Scholarpedia article).	Shant and Alex
Week 10	Oct 29	Towards a General Theory of Neural Computation Based on Prediction by Single Neurons, by Fiorillo. Also read this article's supporting information. Synthesis of nonlinear control surfaces by a layered associative search network, by Barto, Anderson, and Sutton	Kate and Chuck
Week 11	Nov 5	Efficient Head Pose Estimation with Gabor Wavelet Networks Sparse inverse covariance estimation with the lasso	John and Malai
Week 12	Nov 12	Greedy Layer-Wise Training of Deep Networks Model-free functional MRI analysis based on unsupervised clustering	Stephen and Mark
Week 13	Nov 19	Theory of Monte Carlo Sampling-Based Alopex Algorithms for Neural Networks Active Wavelet Networks for Face Alignment'	Elliott and John	Project proposals due in class. They must be at least 5 single-spaced pages. Include descriptions of Problem you want to address. Why this interests you. Objectives of your project. Be brief, but concrete. Approach you will take, in as much detail as possible at this point. Expected results. Milestones with dates. Must be at least 4 milestones. References. Your proposal must cite relevant literature.
Week 14	Dec 3	Two paper reviews (45 minutes each) and two Project Proposal Presentations (15 minutes each) Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data Liquid computing	Reviews by Mike and Alex.
Week 15	Dec 10	Eight Project Proposal Presentations (15 minutes each)

Other possible papers, most recently found first.

?	Self-Optimizing Memory Controllers: A Reinforcement Learning Approach, by Ipek,et al.
?	Extreme Components Analysis, by Welling et al.
?	A model for learning to segment temporal sequences, utilizing a mixture of RNN experts together with adaptive variance, by Namikawa and Tani
?	Supervised Locality Preserving Indexing for Text Categorization, by Han Liu
?	Feature Generation by Simple-FLDA for Pattern Recognition, by Fukumi et al., CIMCA'2005, Vol.2, pp.730-734, Vienna, Austria (2005)
?	A novel dimensionality-reduction approach for face recognition, by Fengxi Song
?	Techniques for extracting single-trial activity patterns from large-scale neural recordings, by Mark M Churchland
?	The Dynamic Brain: From Spiking Neurons to Neural Masses and Cortical Fields
?	The Neural Correlates of Desire
?	Mapping the Structural Core of Human Cerebral Cortex
?	Beyond mind-reading: multi-voxel pattern analysis of fMRI data
?	Computational models of schizophrenia and dopamine modulation in the prefrontal cortex
?	The temporal precision of reward prediction in dopamine neurons
?	Task difficulty modulates the activity of specific neuronal populations in primary visual cortex
?	Decision-making with multiple alternatives
?	Reward prediction based on stimulus categorization in primate lateral prefrontal cortex
?	Unconscious determinants of free decisions in the human brain
?	Theta phase–specific codes for two-dimensional position, trajectory and heading in the hippocampus
?	Focus on decision making and Modulators of decision making
?	Top-down laminar organization of the excitatory network in motor cortex
?	Molecular and electrophysiological evidence for net synaptic potentiation in wake and depression in sleep
?	Reactivation of experience-dependent cell assembly patterns in the hippocampus
?	Prefrontal cortex and basal ganglia control access to working memory
?	Spatio-temporal correlations and visual signalling in a complete neuronal population
?