default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDNIPS 2008: Vancouver, British Columbia, Canada
- Daphne Koller, Dale Schuurmans, Yoshua Bengio, Léon Bottou:
Advances in Neural Information Processing Systems 21, Proceedings of the Twenty-Second Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 8-11, 2008. Curran Associates, Inc. 2009 - Daniel E. Acuna, Paul R. Schrater:
Structure Learning in Human Sequential Decision-Making. 1-8 - Ryan Prescott Adams, Iain Murray, David J. C. MacKay:
The Gaussian Process Density Sampler. 9-16 - Deepak Agarwal, Bee-Chung Chen, Pradheep Elango, Nitin Motgi, Seung-Taek Park, Raghu Ramakrishnan, Scott Roy, Joe Zachariah:
Online Models for Content Optimization. 17-24 - Nir Ailon:
Reconciling Real Scores with Binary Comparisons: A New Logistic Based Model for Ranking. 25-32 - Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, Eric P. Xing:
Mixed Membership Stochastic Blockmodels. 33-40 - Ijaz Akhter, Yaser Sheikh, Sohaib Khan, Takeo Kanade:
Nonrigid Structure from Motion in Trajectory Space. 41-48 - Norm Aleks, Stuart Russell, Michael G. Madden, Diane Morabito, Kristan Staudenmayer, Mitchell J. Cohen, Geoffrey T. Manley:
Probabilistic detection of short events, with application to critical care monitoring. 49-56 - Mauricio A. Álvarez, Neil D. Lawrence:
Sparse Convolved Gaussian Processes for Multi-output Regression. 57-64 - Massih-Reza Amini, François Laviolette, Nicolas Usunier:
A Transductive Bound for the Voted Classifier with an Application to Semi-supervised Learning. 65-72 - Cédric Archambeau, Francis R. Bach:
Sparse probabilistic projections. 73-80 - Arthur U. Asuncion, Padhraic Smyth, Max Welling:
Asynchronous Distributed Learning of Topic Models. 81-88 - Peter Auer, Thomas Jaksch, Ronald Ortner:
Near-optimal Regret Bounds for Reinforcement Learning. 89-96 - Joseph L. Austerweil, Thomas L. Griffiths:
Analyzing human feature learning as nonparametric Bayesian inference. 97-104 - Francis R. Bach:
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning. 105-112 - J. Andrew Bagnell, David M. Bradley:
Differentiable Sparse Coding. 113-120 - Shai Ben-David, Margareta Ackerman:
Measures of Clustering Quality: A Working Set of Axioms for Clustering. 121-128 - Pietro Berkes
, Frank D. Wood, Jonathan W. Pillow:
Characterizing neural dependencies with copula models. 129-136 - Patrice Bertail, Stéphan Clémençon, Nicolas Vayatis:
On Bootstrapping the ROC Curve. 137-144 - Steffen Bickel, Christoph Sawade, Tobias Scheffer:
Transfer Learning by Distribution Matching for Targeted Advertising. 145-152 - Matthew B. Blaschko, Arthur Gretton:
Learning Taxonomies by Dependence Maximization. 153-160 - Phil Blunsom, Trevor Cohn, Miles Osborne:
Bayesian Synchronous Grammar Induction. 161-168 - Matthew M. Botvinick, James An:
Goal-directed decision making in prefrontal cortex: a computational framework. 169-176 - Alexandre Bouchard-Côté, Michael I. Jordan, Dan Klein:
Efficient Inference in Phylogenetic InDel Trees. 177-184 - Jordan L. Boyd-Graber, David M. Blei:
Syntactic Topic Models. 185-192 - Alexander Braunstein, Zhi Wei, Shane T. Jensen, Jon D. McAuliffe:
A spatially varying two-sample recombinant coalescent, with applications to HIV escape response. 193-200 - Sébastien Bubeck, Rémi Munos, Gilles Stoltz, Csaba Szepesvári:
Online Optimization in X-Armed Bandits. 201-208 - Charles F. Cadieu, Bruno A. Olshausen:
Learning Transformational Invariants from Natural Movies. 209-216 - Ben Calderhead, Mark A. Girolami, Neil D. Lawrence:
Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes. 217-224 - Guangzhi Cao, Charles A. Bouman:
Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform. 225-232 - Peter Carbonetto, Mark Schmidt, Nando de Freitas:
An interior-point stochastic approximation method and an L1-regularized delta rule. 233-240 - Rui M. Castro, Charles Kalish, Robert D. Nowak, Ruichen Qian, Timothy T. Rogers, Xiaojin Zhu:
Human Active Learning. 241-248 - Giovanni Cavallanti, Nicolò Cesa-Bianchi, Claudio Gentile:
Linear Classification and Selective Sampling Under Low Noise Conditions. 249-256 - Volkan Cevher, Marco F. Duarte, Chinmay Hegde, Richard G. Baraniuk:
Sparse Signal Recovery Using Markov Random Fields. 257-264 - Kian Ming Adam Chai, Christopher K. I. Williams, Stefan Klanke, Sethu Vijayakumar:
Multi-task Gaussian Process Learning of Robot Inverse Dynamics. 265-272 - Deepayan Chakrabarti, Ravi Kumar, Filip Radlinski, Eli Upfal:
Mortal Multi-Armed Bandits. 273-280 - Olivier Chapelle, Chuong B. Do, Quoc V. Le, Alexander J. Smola, Choon Hui Teo:
Tighter Bounds for Structured Estimation. 281-288 - Kamalika Chaudhuri, Claire Monteleoni:
Privacy-preserving logistic regression. 289-296 - Silvia Chiappa, Jens Kober, Jan Peters:
Using Bayesian Dynamical Systems for Motion Template Libraries. 297-304 - Stéphan Clémençon, Nicolas Vayatis:
Empirical performance maximization for linear rank statistics. 305-312 - Stéphan Clémençon, Nicolas Vayatis:
Overlaying classifiers: a practical approach for optimal ranking. 313-320 - Shay B. Cohen, Kevin Gimpel, Noah A. Smith:
Logistic Normal Priors for Unsupervised Probabilistic Grammar Induction. 321-328 - Kevyn Collins-Thompson:
Estimating Robust Query Models with Convex Optimization. 329-336 - Pierre-Arnaud Coquelin, Romain Deguest, Rémi Munos:
Particle Filter-based Policy Gradient in POMDPs. 337-344 - Koby Crammer, Mark Dredze, Fernando Pereira:
Exact Convex Confidence-Weighted Learning. 345-352 - Wenyuan Dai, Yuqiang Chen, Gui-Rong Xue, Qiang Yang, Yong Yu:
Translated Learning: Transfer Learning across Different Feature Spaces. 353-360 - Sanmay Das, Malik Magdon-Ismail:
Adapting to a Market Shock: Optimal Sequential Market-Making. 361-368 - Peter Dayan:
Load and Attentional Bayes. 369-376 - Ofer Dekel:
From Online to Batch Learning with Cutoff-Averaging. 377-384 - Dotan Di Castro, Dmitry Volkinshtein, Ron Meir:
Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation. 385-392 - Doug Downey, Oren Etzioni:
Look Ma, No Hands: Analyzing the Monotonic Feature Abstraction for Text Classification. 393-400 - Miroslav Dudík, Steven J. Phillips:
Generative and Discriminative Learning with Unknown Labeling Bias. 401-408 - Laurent El Ghaoui, Assane Gueye:
A Convex Upper Bound on the Log-Partition Function for Binary Distributions. 409-416 - Gal Elidan, Stephen Gould:
Learning Bounded Treewidth Bayesian Networks. 417-424 - Dominik Endres, Peter Földiák:
Interpreting the neural code with Formal Concept Analysis. 425-432 - Lev Faivishevsky, Jacob Goldberger:
ICA based on a Smooth Estimation of the Differential Entropy. 433-440 - Amir Massoud Farahmand, Mohammad Ghavamzadeh, Csaba Szepesvári, Shie Mannor:
Regularized Policy Iteration. 441-448 - Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal:
Resolution Limits of Sparse Coding in High Dimensions. 449-456 - Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky:
Nonparametric Bayesian Learning of Switching Linear Dynamical Systems. 457-464 - Paolo Frasconi, Andrea Passerini:
Predicting the Geometry of Metal Binding Sites from Protein Sequence. 465-472 - Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf:
Characteristic Kernels on Groups and Semigroups. 473-480 - C. C. Alan Fung, K. Y. Michael Wong, Si Wu:
Tracking Changing Stimuli in Continuous Attractor Neural Networks. 481-488 - Pierre Garrigues, Laurent El Ghaoui:
An Homotopy Algorithm for the Lasso with Online Observations. 489-496 - Jan Gasthaus, Frank D. Wood, Dilan Görür, Yee Whye Teh:
Dependent Dirichlet Process Spike Sorting. 497-504 - Sharad Goel, John Langford, Alexander L. Strehl:
Predictive Indexing for Fast Search. 505-512 - Vicenç Gómez, Andreas Kaltenbrunner, Vicente López, Hilbert J. Kappen:
Self-organization using synaptic plasticity. 513-520 - Dilan Görür, Yee Whye Teh:
An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering. 521-528 - Hans Peter Graf, Srihari Cadambi, Igor Durdanovic, Venkata Jakkula, Murugan Sankaradass, Eric Cosatto, Srimat T. Chakradhar:
A Massively Parallel Digital Learning Processor. 529-536 - Yves Grandvalet, Alain Rakotomamonjy, Joseph Keshet, Stéphane Canu:
Support Vector Machines with a Reject Option. 537-544 - Alex Graves, Jürgen Schmidhuber:
Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks. 545-552 - Thomas L. Griffiths, Christopher G. Lucas, Joseph Jay Williams, Michael L. Kalish:
Modeling human function learning with Gaussian processes. 553-560 - Moritz Grosse-Wentrup:
Understanding Brain Connectivity Patterns during Motor Imagery for Brain-Computer Interfacing. 561-568 - Yuhong Guo:
Supervised Exponential Family Principal Component Analysis via Convex Optimization. 569-576 - Abhinav Gupta, Jianbo Shi, Larry S. Davis:
A "Shape Aware" Model for semi-supervised Learning of Objects and its Context. 577-584 - Ralf M. Haefner, Bruce G. Cumming:
An improved estimator of Variance Explained in the presence of noise. 585-592 - Adrian Haith, Carl P. T. Jackson, R. Chris Miall, Sethu Vijayakumar:
Unifying the Sensory and Motor Components of Sensorimotor Adaptation. 593-600 - Jihun Ham, Daniel D. Lee:
Extended Grassmann Kernels for Subspace-Based Learning. 601-608 - Zaïd Harchaoui, Francis R. Bach, Eric Moulines:
Kernel Change-point Analysis. 609-616 - Stefan Haufe, Vadim V. Nikulin, Andreas Ziehe, Klaus-Robert Müller, Guido Nolte:
Estimating vector fields using sparse basis field expansions. 617-624 - Xuming He, Richard S. Zemel:
Learning Hybrid Models for Image Annotation with Partially Labeled Data. 625-632 - Geremy Heitz, Gal Elidan, Benjamin Packer, Daphne Koller:
Shape-Based Object Localization for Descriptive Classification. 633-640 - Geremy Heitz, Stephen Gould, Ashutosh Saxena, Daphne Koller:
Cascaded Classification Models: Combining Models for Holistic Scene Understanding. 641-648 - Mark Herbster, Guy Lever, Massimiliano Pontil:
Online Prediction on Large Diameter Graphs. 649-656 - Mark Herbster, Massimiliano Pontil, Sergio Rojas Galeano:
Fast Prediction on a Tree. 657-664 - N. Jeremy Hill, Jason Farquhar, Suzanna Martens, Felix Bießmann, Bernhard Schölkopf:
Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance. 665-672 - Michael P. Holmes, Alexander G. Gray, Charles Lee Isbell Jr.:
QUIC-SVD: Fast SVD Using Cosine Trees. 673-680 - Xiaodi Hou, Liqing Zhang:
Dynamic visual attention: searching for coding length increments. 681-688 - Patrik O. Hoyer, Dominik Janzing, Joris M. Mooij, Jonas Peters, Bernhard Schölkopf:
Nonlinear causal discovery with additive noise models. 689-696 - Jim C. Huang, Brendan J. Frey:
Structured ranking learning using cumulative distribution networks. 697-704 - Ling Huang, Donghui Yan, Michael I. Jordan, Nina Taft:
Spectral Clustering with Perturbed Data. 705-712 - Juan Huo, Zhijun Yang, Alan F. Murray:
Bio-inspired Real Time Sensory Map Realignment in a Robotic Barn Owl. 713-720 - Zakria Hussain, John Shawe-Taylor:
Theory of matching pursuit. 721-728 - Quentin J. M. Huys, Joshua T. Vogelstein, Peter Dayan:
Psychiatry: Insights into depression through normative decision-making models. 729-736 - Michael Isard, John MacCormick, Kannan Achan:
Continuously-adaptive discretization for message-passing algorithms. 737-744 - Laurent Jacob, Francis R. Bach, Jean-Philippe Vert:
Clustered Multi-Task Learning: A Convex Formulation. 745-752 - Srikanth Jagabathula, Devavrat Shah:
Inferring rankings under constrained sensing. 753-760 - Prateek Jain, Brian Kulis, Inderjit S. Dhillon, Kristen Grauman:
Online Metric Learning and Fast Similarity Search. 761-768 - Viren Jain, H. Sebastian Seung:
Natural Image Denoising with Convolutional Networks. 769-776 - Shuiwang Ji, Liang Sun, Rong Jin, Jieping Ye:
Multi-label Multiple Kernel Learning. 777-784 - Matt Jones, Michael C. Mozer, Sachiko Kinoshita:
Optimal Response Initiation: Why Recent Experience Matters. 785-792 - Sham M. Kakade, Karthik Sridharan, Ambuj Tewari:
On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization. 793-800 - Sham M. Kakade, Ambuj Tewari:
On the Generalization Ability of Online Strongly Convex Programming Algorithms. 801-808 - Takafumi Kanamori, Shohei Hido, Masashi Sugiyama:
Efficient Direct Density Ratio Estimation for Non-stationarity Adaptation and Outlier Detection. 809-816 - Kentaro Katahira, Jun Nishikawa, Kazuo Okanoya, Masato Okada:
Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM. 817-824 - Charles Kemp, Fei Xu:
An ideal observer model of infant object perception. 825-832 - JooSeuk Kim, Clayton D. Scott:
Performance analysis for L_2 kernel classification. 833-840 - Tae-Kyun Kim, Roberto Cipolla:
MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual Features. 841-856 - Jens Kober, Jan Peters:
Policy Search for Motor Primitives in Robotics. 849-856 - Christoph Kolodziejski, Bernd Porr, Minija Tamosiunaite, Florentin Wörgötter:
On the asymptotic equivalence between differential Hebbian and temporal difference learning using a local third factor. 857-864 - Nikos Komodakis, Nikos Paragios, Georgios Tziritas:
Clustering via LP-based Stabilities. 865-872 - Lukas Kroc, Ashish Sabharwal, Bart Selman:
Counting Solution Clusters in Graph Coloring Problems Using Belief Propagation. 873-880 - Pavel P. Kuksa, Pai-Hsi Huang, Vladimir Pavlovic:
Scalable Algorithms for String Kernels with Inexact Matching. 881-888 - M. Pawan Kumar, Philip H. S. Torr:
Improved Moves for Truncated Convex Models. 889-896 - Simon Lacoste-Julien, Fei Sha, Michael I. Jordan:
DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification. 897-904 - John Langford, Lihong Li, Tong Zhang:
Sparse Online Learning via Truncated Gradient. 905-912 - Longin Jan Latecki, ChengEn Lu, Marc Sobel, Xiang Bai:
Multiscale Random Fields with Application to Contour Grouping. 913-920 - Jonathan Le Roux, Alain de Cheveigné, Lucas C. Parra:
Adaptive Template Matching with Shift-Invariant Semi-NMF. 921-928 - Dongryeol Lee, Alexander G. Gray:
Fast High-dimensional Kernel Summations Using the Monte Carlo Multipole Method. 929-936 - Roger Levy, Florencia Reali, Thomas L. Griffiths:
Modeling the effects of memory on human online sentence processing with particle filters. 937-944 - Jeremy Lewi, Robert J. Butera, David M. Schneider, Sarah M. N. Woolley, Liam Paninski:
Designing neurophysiology experiments to optimally constrain receptive field models along parametric submanifolds. 945-952 - Ping Li, Kenneth Ward Church, Trevor Hastie:
One sketch for all: Theory and Application of Conditional Random Sampling. 953-960 - Yen-Yu Lin, Tyng-Luh Liu, Chiou-Shann Fuh:
Dimensionality Reduction for Data in Multiple Feature Representations. 961-968 - Han Liu, John D. Lafferty, Larry A. Wasserman:
Nonparametric regression and classification with joint sparsity constraints. 969-976 - Philip M. Long, Rocco A. Servedio:
Adaptive Martingale Boosting. 977-984 - Christopher G. Lucas, Thomas L. Griffiths, Fei Xu, Christine Fawcett:
A rational model of preference learning and choice prediction by children. 985-992 - Elliot A. Ludvig, Richard S. Sutton, Eric Verbeek, E. James Kehoe:
A computational model of hippocampal function in trace conditioning. 993-1000 - Gediminas Luksys, Carmen Sandi, Wulfram Gerstner:
Stress, noradrenaline, and realistic prediction of mouse behaviour using reinforcement learning. 1001-1008