Overview | Program Highlights | Tutorials | Conference Sessions | Workshops | Demonstrations | Accepted Papers | Committee 2008
Posters
7:30pm - 12:00am Tuesday, December 09, 2008
Tuesday Poster Layout- A. Farahmand, M. Ghavamzadeh, C. Szepesvari, S. Mannor: Regularized Policy Iteration
- P. Auer, T. Jaksch, R. Ortner: Near-optimal Regret Bounds for Reinforcement Learning
- G. Neumann, J. Peters: Fitted Q-iteration by Advantage Weighted Regression
- J. Roberts, R. Tedrake: Signal-to-Noise Ratio Analysis of Policy Gradient Algorithms
- J. Kober, J. Peters: Policy Search for Motor Primitives in Robotics
- E. Talvitie, S. Singh: Simple Local Models for Complex Dynamical Systems
- K. Chai, C. Williams, S. Klanke, S. Vijayakumar: Multi-task Gaussian Process Learning of Robot Inverse Dynamics
- Y. Wang, J. Audibert, R. Munos: Algorithms for Infinitely Many-Armed Bandits
- A. Nouri, M. Littman: Multi-resolution Exploration in Continuous Spaces
- L. Zettlemoyer, B. Milch, L. Kaelbling: Multi-Agent Filtering with Infinitely Nested Beliefs
- A. Haith, C. Jackson, R. Miall, S. Vijayakumar: Unifying the Sensory and Motor Components of Sensorimotor Adaptation
- I. Sutskever, G. Hinton, G. Taylor: The Recurrent Temporal Restricted Boltzmann Machine
- P. Ruvolo, I. Fasel, j. movellan: Optimization on a Budget: A Reinforcement Learning Approach
- M. Streeter, D. Golovin: An Online Algorithm for Maximizing Submodular Functions
- P. Jain, B. Kulis, I. Dhillon, K. Grauman: Online Metric Learning and Fast Similarity Search
- M. Herbster, M. Pontil, S. Rojas Galeano: Fast Prediction on a Tree
- Y. Tam, T. Schultz: Correlated Bigram LSA for Unsupervised Language Model Adaptation
- Y. Zhang, J. Schneider, A. Dubrawski: Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text
- A. Mnih, G. Hinton: A Scalable Hierarchical Distributed Language Model
- O. Chapelle, C. Do, Q. Le, A. Smola, C. Teo: Tighter Bounds for Structured Estimation
- D. Weinshall, H. Hermansky, A. Zweig, J. Luo, H. Jimison, F. Ohl, M. Pavel: Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree
- A. Singh, R. Nowak, X. Zhu: Unlabeled data: Now it helps, now it doesn't
- J. Tam, J. Simsa, S. Hyde, L. von Ahn: Breaking Audio CAPTCHAs with Machine Learning Techniques
- M. Amini, N. Usunier, F. Laviolette: A Transductive Bound for the Voted Classifier with an Application to Semi-supervised Learning
- R. Nock, F. NIELSEN: On the Efficient Minimization of Classification Calibrated Surrogates
- K. Crammer, M. Dredze, F. Pereira: Exact Convex Confidence-Weighted Learning
- Z. Xu, R. Jin, I. King, M. Lyu: An Extended Level Method for Efficient Multiple Kernel Learning
- G. Elidan, S. Gould: Learning Bounded Treewidth Bayesian Networks
- B. Yackley, E. Corona, T. Lane: Bayesian Network Score Approximation using a Metagraph Kernel
- J. Zhu, E. Xing, B. Zhang: Partially Observed Maximum Entropy Discrimination Markov Networks
- M. Raginsky, S. Lazebnik, R. Willett, J. Silva: Near-minimax recursive density estimation on the binary hypercube
- Y. Grandvalet, J. Keshet, A. Rakotomamonjy, S. Canu: Suppport Vector Machines with a Reject Option
- J. Langford, L. Li, T. Zhang: Sparse Online Learning via Truncated Gradient
- S. Kakade, A. Tewari: On the Generalization Ability of Online Strongly Convex Programming Algorithms
- A. Rahimi, B. Recht: Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learning
- H. Masnadi-Shirazi, N. Vasconcelos: On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoost
- G. Cavallanti, N. Cesa-Bianchi, C. Gentile: Linear Classification and Selective Sampling Under Low Noise Conditions
- O. Dekel: From Online to Batch Learning with Cutoff-Averaging
- P. Long, R. Servedio: Adaptive Martingale Boosting
- S. Shalev-Shwartz, S. Kakade: Mind the Duality Gap: Logarithmic regret algorithms for online optimization
- P. Bertail, S. Clémençon, N. Vayatis: On Bootstrapping the ROC Curve
- S. Lacoste-Julien, F. Sha, M. Jordan: DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification
- Z. Zhang, M. Jordan, D. Yeung: Posterior Consistency of the Silverman g-prior in Bayesian Model Choice
- Y. Lin, T. Liu, C. Fuh: Dimensionality Reduction for Data in Multiple Feature Representations
- V. Jain, H. Seung: Natural Image Denoising with Convolutional Networks
- A. Fletcher, S. Rangan, V. Goyal: Resolution Limits of Sparse Coding in High Dimensions
- N. Schraudolph, D. Kamenetsky: Efficient Exact Inference in Planar Ising Models
- M. Opper, U. Paquet, O. Winther: Improving on Expectation Propagation
- N. Ailon: Reconciling Real Scores with Binary Comparisons: A Unified Logistic Model for Ranking
- M. Titsias, N. Lawrence, M. Rattray: Efficient Sampling for Gaussian Process Inference using Control Variables
- Y. Wexler, C. Meek: MAS: a multiplicative approximation scheme for probabilistic inference
- R. Adams, I. Murray, D. MacKay: The Gaussian Process Density Sampler
- M. Seeger, H. Nickisch, R. Pohmann, B. Schölkopf: Bayesian Experimental Design of Magnetic Resonance Imaging Sequences
- J. Mooij, H. Kappen: Bounds on marginal probability distributions
- D. Sontag, A. Globerson, T. Jaakkola: Clusters and Coarse Partitions in LP Relaxations
- T. Kim, R. Cipolla: MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual Features
- X. He, R. Zemel: Learning Hybrid Models for Image Annotation with Partially Labeled Data
- P. Srinivasan, L. Wang, J. Shi: Grouping Contours Via a Related Image
- P. Mudigonda, P. Torr: Improved Moves for Truncated Convex Models
- F. Bach: Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning
- P. Hoyer, D. Janzing, J. Mooij, J. Peters, B. Schölkopf: Nonlinear causal discovery with additive noise models
- P. Frasconi, A. Passerini: Predicting the Geometry of Metal Binding Sites from Protein Sequence
- G. Quon, Y. Teh, E. Chan, M. Brudno, T. Hughes, Q. Morris: A mixture model for the evolution of gene expression in non-homogeneous datasets
- N. Aleks, S. Russell, M. Madden, D. Morabito, G. Manley, K. Staudenmayer, M. Cohen: Probabilistic detection of short events, with application to critical care monitoring
- L. Shpigelman, H. Lalazar, E. Vaadia: Kernel-ARMA for Hand Tracking and Brain-Machine interfacing During 3D Motor Control
- M. Tangermann (ne Schröder), M. Krauledat, K. Grzeska, M. Sagebaum, B. Blankertz, K. Muller: Playing Pinball with non-invasive BCI
- H. Graf, H. Cadambi, I. Durdanovic, V. Jakkula, M. Sankaradass, E. Cosatto, S. Chakradhar: A Massively Parallel Digital Learning Processor
- J. Hill, J. Farquhar, S. Martens, F. Bießmann, B. Schölkopf: Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance
- J. Austerweil, T. Griffiths: Analyzing human feature learning as nonparametric Bayesian inference
- G. Luksys, C. Sandi, W. Gerstner: Stress, noradrenaline, and realistic prediction of mouse behaviour using reinforcement learning
- K. Katahira, J. Nishikawa, K. Okanoya, M. Okada: A Bayesian Approach for Extracting State Transition Dynamics from Multiple Spike Trains
- D. Acuna, P. Schrater: Structure Learning in Human Sequential Decision-Making
- J. Gasthaus, F. Wood, D. Gorur, Y. Teh: Dependent Dirichlet Process Spike Sorting
- M. Jones, M. Mozer, S. Kinoshita: Optimal Response Initiation: Why Recent Experience Matters
- J. Xu, T. Griffiths: How memory biases affect information transmission: A rational analysis of serial reproduction
- A. Yu, J. Cohen: Sequential effects: Superstition or rational behavior?
- C. Lucas, T. Griffiths, F. Xu, C. Fawcett: A rational model of preference learning and choice prediction by children
- M. Todd, Y. Niv, J. Cohen: Learning to Use Working Memory in Partially Observable Environments through Dopaminergic Reinforcement
- K. Wimmer, M. Stimberg, R. Martin, L. Schwabe, J. Mariño, J. Schummers, D. Lyon, M. Sur, K. Obermayer: Dependence of Orientation Tuning on Recurrent Excitation and Inhibition in a Network Model of V1
- Q. Huys, j. vogelstein, P. Dayan: Depression: an RL formulation and a behavioural test