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NIPS Online

Learning@Snowbird 2005: Program


  • Dan Huttenlocher Cornell, Graphical Models for Object Recognition
  • Michael Kearns U. Penn, Game Theory, Economics, and the Effects of Network Structure
  • Larry Matthies NASA/JPL, Perception for Autonomous Navigation Off-road and Off-planet
  • Denis Pelli NYU, Human vision isolates parts to recognize the whole


003P. Baldi (University of California, Irvine)
Kernels for Small Molecules and the Prediction of Mutagenicity, Toxity, and Anti-Cancer Activity
004Ashok Veeraraghavan(University of Maryland) and Rama Chellappa(University of Maryland)
Tracking Bees in a Hive
008E. Mjolsness (UCI)
Variable-structure systems from dependency diagrams and dynamical grammars
009Ahmad Emami (Johns Hopkins University), Frederick Jelinek (Johns Hopkins University)
Random Clusterings for Language Modeling
011H.P. Graf, E. Cosatto, I. Durdanovic, NEC Laboratories, 4 Independence Way, Princeton, NJ 08450
Parallel Computing and SVMs
012S. Osindero (U. Toronto) & G. E. Hinton (U. Toronto)
Learning Causal Hierarchies And Hidden Markov Random Fields
014O.P. Kreidl, M. Cetin and A.S. Willsky (MIT)
Collaborative Distributed Inference with Minimal Online Communication
015H.J. Kappen
A variational approach to planning and control
016A.X. Zheng (UC Berkeley), M.I. Jordan (UC Berkeley), B. Liblit (U. Wisconsin), M. Naik (Stanford), A. Aiken (Stanford)
Statistical Debugging: A Case Study
027S. Kakade (University of Pennsylvania) and M. Kearns (University of Pennsylvania)
Trading in Markovian Price Models
029Wolfram Burgard (U. Freiburg) and Cyrill Stachniss (U. Freiburg) and Giorgio Grisetti (U. Rome)
Information Gain-based Exploration Using Rao-Blackwellized Particle Filters
030M. Keller (IDIAP), and S. Bengio (IDIAP)
A Neural Network for Text Representation
031Yann LeCun, Fu Jie Huang (Courant Institute, NYU)
Loss Functions for Energy-Based Models
034G. Blanchard (Fraunhofer FIRST, Berlin), M. Kawanabe (Fraunhofer FIRST), M. Sugiyama (Tokyo Institute of technology), V. Spokoiny (Weierstrass Institut, Berlin), K-R. Müller (Fraunhofer FIRST)
Finding interesting parts of multidimensional data via identification of non-Gaussian linear subspaces
044Sara C. Madeira (INESC-ID/University of Beira interior), and Arlindo L. Oliveira (INESC-ID/IST)
A Linear Time Biclustering Algorithm for Time Series Gene Expression Data
049Baback Moghaddam (MERL), Yair Weiss (Hebrew U.) and Shai Avidan (MERL)
Combinatorial Algorithms for Sparse PCA
050H. Schwenk (LIMSI-CNRS), and J.-L. Gauvain (LIMSI-CNRS)
Large Scale Applications of the Neural Network Language Model
058Raffay Hamid, Siddhartha Maddi, Amos Johnson, Aaron Bobick, Irfan Essa, Charles Isbell
Unsupervised Activity Discovery and Characterization From Event-Streams
059G. Gordon (CMU)
No-regret algorithms for structured prediction problems
060Rich Caruana and Alex Niculescu
Predicting Good Probabilities
061F. Dellaert (Georgia Tech)
Cholesky and QR Factorization Coupled with Loopy Belief Propagation in Large-Scale Gaussian Markov Random Fields
062F. Sha (U. of Pennsylvania), and L. K. Saul (U. of Pennsylvania)
Conformal Dimensionality Reduction
064N. Srebro (U. Toronto) and S. Roweis (U. Toronto)
Adaptive Gaussian Kernel SVMs
068R. de Salvo Braz, R. Girju, V. Punyakanok, D. Roth, M. Sammons (University of Illinois, Urbana)
An Inference Model for Semantic Entailment in Natural Language
075V. Cheung (U. Toronto), B. J. Frey (U. Toronto), and N. Jojic (Microsoft Research)
Video Epitomes
077A. Beygelzimer (IBM Research), Sham Kakade (U. Penn), John Langford (TTI-Chicago)
Cover Trees for Nearest Neighbor
086C. Sutton and A. McCallum (U. of Massachusetts)
Local and Global Normalization in Graphical Parameter Estimation
089Yoshua Bengio, Olivier Delalleau and Nicolas Le Roux (Université de Montréal)
The Curse of Dimensionality for Local Kernel Machines
097S. Ben-David, University of Waterloo
A Notion of Stability for Sample Based Clustering


001M. Isard, J. MacCormick (Microsoft Research)
Multi-scale loopy belief propagation for stereo vision and optic flow
002Lei Xu (Chinese University of Hong Kong)
BYY Harmony Learning, Automatic Model Selection, and Comparative Studies
005S. Macskassy (NYU) and F. Provost (NYU)
NetKit-SRL: A Network Learning Toolkit for Statistical Relational Learning
006S. Hochreiter (TU Berlin), and K. Obermayer (TU Berlin)
Unsupervised Learning with Optimal Kernels
007Greg Shakhnarovich and Trevor Darrell (MIT)
Learning task-specific visual similarity
010Ariadna Quattoni, Michael Collins, Trevor Darrell ( CSAIL MIT)
Conditional Random Fields for Object Recognition
013D. D. Lee, H. Rubin, and V. Kumar (U. Pennsylvania)
Cellular-Inspired Garbage Collection and Recognition
017S. Lazebnik (UIUC Beckman Institute), C. Schmid (INRIA Rhone-Alpes), and J. Ponce (UIUC Beckman Institute)
A Maximum Entropy Framework for Combining Parts and Relations for Texture and Object Recognition
018B. Limketkai, L. Liao, D. Fox (all University of Washington)
Relational Object Maps for Mobile Robots
021Sumit Chopra, Raia Hadsell, Yann LeCun (Courant Institute, NYU)
Learning a Similarity Metric Discriminatively, with Application to Face Verification
023C.Alippi (Politecnico di Milano), D.Cogliati (Politecnico di Milano)
024F. Fleuret (EPFL), W. Gerstner (EPFL)
A Bayesian Kernel for the Prediction of Neuron Properties from Binary Gene Profiles
026C. Alippi (Politecnico di Milano), D. Cogliati (Politecnico di Milano), C.Galperti (Politecnico di Milano), E. Pasero (Politecnico di Torino)
032A. Goulon (ESPCI, Paris), A. Duprat (ESPCI, Paris), G. Dreyfus (ESPCI, Paris)
Graph machines
033C. Garcia (France Telecom division R&D)
A Connexionnist Approach for Robust and Precise Facial Feature Detection in Complex Scenes
035A. Kapoor (MIT), and Yuan (Alan) Qi (MIT), and Rosalind W. Picard (MIT)
Bayesian Semi-Supervised Classification
037W. Dong, M. Martin, and A. Pentland (MIT)
Using the Influence Model to Capture Group Interactions
038Tulay Adali (University of Maryland Baltimore County)
Signal Processing with Complex Nonlinearities
039C. Dima and M. Hebert (CMU)
Pool-based Active Learning with Data Block
040S. Hochreiter (TU Berlin), and K. Obermayer (TU Berlin)
Sequence Classification For Protein Analysis
041Lawrence Carin, Nilanjan Dasgupta, Shaorong Chang, Yuting Qi (Duke University)
Variational Bayes and Expectation Propagation for Unsupervised Feature Selection, Clustering and Density Estimation
045Y. Bengio (U. Montreal) and H. Larochelle (U. Montreal)
Non-Local Manifold Parzen Windows
046N. Le Roux (U. de Montreal), Y. Bengio (U. de Montreal) and R. Ducharme (U. de Montreal)
Combining density estimators to improve classification performance
048John Kaufhold, Pascale Rondot, Roderic Collins, and Anthony Hoogs (all from GE Research)
Multiclass Boosting on Region Graphs Applied to Aerial Video Content Recognition
053Andrew I. Schein (U. Pennsylvania) and Lyle H. Ungar (U. Pennsylvania)
Active Learning for Multi-Class Logistic Regression
054A. Fraser, N. Hengartner, K. Vixie and B. Wohlberg (Los Alamos National Laboratory)
Exploiting Invariants for Classification with Application to Face Recognition
055N. Efron (Tel-Aviv U), and N. Intrator (Tel-Aviv U.)
Stabilizing Methods for Ill-Conditioned LDA, with Applications to Gene Expression Data
057D. Remondini, B. O’Connell, (Bologna U), N. Intrator (Tel-Aviv U.), . M. Sedivy, N. Neretti, G. C. Castellani and L. N Cooper (Brown U.)
Targeting c-Myc Activated Genes via Correlation and Markov Modeling
066R. C. Venkatesan (Systems Research Corporation)
ICA through a Fisher game
067Vasin Punyakanok, Dan Roth, Wen-tau Yih, Dav Zimak (University of Illinois, Urbana)
Learning and Inference over Constrained Output
069Milind Mahajan (Microsoft Research), and Asela Gunawardana (Microsoft Research)
Phone classification using hidden conditional random fields
070G. Grudic and J. Mulligan, University of Colorado at Boulder
Outlier Detection in Manifold Space: Applications to Vision Based Human-to-Robot Skill Transfer and One Class Learning
072Tina Eliassi-Rad (Lawrence Livermore National Laboratory) and Terence Critchlow (Lawrence Livermore National Laboratory)
Similarity in Computational Sciences
073T. Ould Bachir (Ecole Polytechnique de Montreal), J.-J. Brault (Ecole Polytechnique de Montreal)
A Multiplexer-based Device for Simulated Binary Bayesian Networks
074M. Belkin, P. Niyogi, University of Chicago
On Graph and Manifold Laplacians: Towards a Theoretical Foundation
079Pierre-Alexandre Fournier and Jean-Jules Brault (Ecole Polytechnique de Montreal)
Learning the timbre of individuals for realistic speech synthesis
081Shantanu Chakrabartty ( Michigan State University ) and Gert Cauwenberghs ( Johns Hopkins University)
Sequence Learning and Decoding in Margin Propagation Networks
082V. de Sa (UCSD)
A Spectral Minimizing-Disagreement Algorithm
083R. C. Venkatesan (Systems Research Corporation)
Quantum clustering through a Fisher game
084John Langford (TTI Chicago) and Alina Beygelzimer (IBM Watson Research)
Sensitive Error Correcting Output Codes
087Martial Hue (Ecole des Mines de Paris, France), Jean-Philippe Vert (Ecole des Mines de Paris, France)
Semi-Supervised Ranking, and application to bioinformatics
090Srinivas Bangalore and Patrick Haffner (AT&T Labs-Research)
Classification of very large label sets
092Sung-eok Jeon and Chuanyi Ji, Georgia Tech
Graphical Models for Self-Configuration of Ad-hoc Wireless Networks
093Y. Jing (Georgia Tech), V. Pavlovic (Rutgers), J. M. Rehg (Georgia Tech)
Discriminative Learning Using Boosted Generative Models
094Jan Eichhorn and Olivier Chapelle
Image Categorization with Support Vector Machines: Kernels for Local Image Descriptors
095W. Kim (Georgia Tech), N. Jojic (Microsoft Research), and J. M. Rehg (Georgia Tech)
Epitomic Analysis of Human Motion
096Y. Altun and D. McAllester (TTI-C)
Semi-Supervised Structure Learning
098T. Breuel (U. Kaiserslautern and DFKI)
Approximate vs. Representative Nearest Neighbors
099Valery A. Petrushin (Accenture Technology Labs)
Mining Events in Multi-camera Surveillance Video using Self-organizing Maps

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Questions about the workshop should be sent to Karen Smith, karen@nec-labs.com.