003 | P. Baldi (University of California, Irvine) |
| Kernels for Small Molecules and the Prediction of Mutagenicity, Toxity, and Anti-Cancer Activity |
| |
004 | Ashok Veeraraghavan(University of Maryland) and Rama Chellappa(University of Maryland) |
| Tracking Bees in a Hive |
| |
008 | E. Mjolsness (UCI) |
| Variable-structure systems from dependency diagrams and dynamical grammars |
| |
009 | Ahmad Emami (Johns Hopkins University), Frederick Jelinek (Johns Hopkins University) |
| Random Clusterings for Language Modeling |
| |
011 | H.P. Graf, E. Cosatto, I. Durdanovic, NEC Laboratories, 4 Independence Way, Princeton, NJ 08450 |
| Parallel Computing and SVMs |
| |
012 | S. Osindero (U. Toronto) & G. E. Hinton (U. Toronto) |
| Learning Causal Hierarchies And Hidden Markov Random Fields |
| |
014 | O.P. Kreidl, M. Cetin and A.S. Willsky (MIT) |
| Collaborative Distributed Inference with Minimal Online Communication |
| |
015 | H.J. Kappen |
| A variational approach to planning and control |
| |
016 | A.X. Zheng (UC Berkeley), M.I. Jordan (UC Berkeley), B. Liblit (U. Wisconsin), M. Naik (Stanford), A. Aiken (Stanford) |
| Statistical Debugging: A Case Study |
| |
027 | S. Kakade (University of Pennsylvania) and M. Kearns (University of Pennsylvania) |
| Trading in Markovian Price Models |
| |
029 | Wolfram Burgard (U. Freiburg) and Cyrill Stachniss (U. Freiburg) and Giorgio Grisetti (U. Rome) |
| Information Gain-based Exploration Using Rao-Blackwellized Particle Filters |
| |
030 | M. Keller (IDIAP), and S. Bengio (IDIAP) |
| A Neural Network for Text Representation |
| |
031 | Yann LeCun, Fu Jie Huang (Courant Institute, NYU) |
| Loss Functions for Energy-Based Models |
| |
034 | G. 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 |
| |
044 | Sara 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 |
| |
049 | Baback Moghaddam (MERL), Yair Weiss (Hebrew U.) and Shai Avidan (MERL) |
| Combinatorial Algorithms for Sparse PCA |
| |
050 | H. Schwenk (LIMSI-CNRS), and J.-L. Gauvain (LIMSI-CNRS) |
| Large Scale Applications of the Neural Network Language Model |
| |
058 | Raffay Hamid, Siddhartha Maddi, Amos Johnson, Aaron Bobick, Irfan Essa, Charles Isbell |
| Unsupervised Activity Discovery and Characterization From Event-Streams |
| |
059 | G. Gordon (CMU) |
| No-regret algorithms for structured prediction problems |
| |
060 | Rich Caruana and Alex Niculescu |
| Predicting Good Probabilities |
| |
061 | F. Dellaert (Georgia Tech) |
| Cholesky and QR Factorization Coupled with Loopy Belief Propagation in Large-Scale Gaussian Markov Random Fields |
| |
062 | F. Sha (U. of Pennsylvania), and L. K. Saul (U. of Pennsylvania) |
| Conformal Dimensionality Reduction |
| |
064 | N. Srebro (U. Toronto) and S. Roweis (U. Toronto) |
| Adaptive Gaussian Kernel SVMs |
| |
068 | R. de Salvo Braz, R. Girju, V. Punyakanok, D. Roth, M. Sammons (University of Illinois, Urbana) |
| An Inference Model for Semantic Entailment in Natural Language |
| |
075 | V. Cheung (U. Toronto), B. J. Frey (U. Toronto), and N. Jojic (Microsoft Research) |
| Video Epitomes |
| |
077 | A. Beygelzimer (IBM Research), Sham Kakade (U. Penn), John Langford (TTI-Chicago) |
| Cover Trees for Nearest Neighbor |
| |
086 | C. Sutton and A. McCallum (U. of Massachusetts) |
| Local and Global Normalization in Graphical Parameter Estimation |
| |
089 | Yoshua Bengio, Olivier Delalleau and Nicolas Le Roux (Université de Montréal) |
| The Curse of Dimensionality for Local Kernel Machines |
| |
097 | S. Ben-David, University of Waterloo |
| A Notion of Stability for Sample Based Clustering |
| |
001 | M. Isard, J. MacCormick (Microsoft Research) |
| Multi-scale loopy belief propagation for stereo vision and optic flow |
| |
002 | Lei Xu (Chinese University of Hong Kong) |
| BYY Harmony Learning, Automatic Model Selection, and Comparative Studies |
| |
005 | S. Macskassy (NYU) and F. Provost (NYU) |
| NetKit-SRL: A Network Learning Toolkit for Statistical Relational Learning |
| |
006 | S. Hochreiter (TU Berlin), and K. Obermayer (TU Berlin) |
| Unsupervised Learning with Optimal Kernels |
| |
007 | Greg Shakhnarovich and Trevor Darrell (MIT) |
| Learning task-specific visual similarity |
| |
010 | Ariadna Quattoni, Michael Collins, Trevor Darrell ( CSAIL MIT) |
| Conditional Random Fields for Object Recognition |
| |
013 | D. D. Lee, H. Rubin, and V. Kumar (U. Pennsylvania) |
| Cellular-Inspired Garbage Collection and Recognition |
| |
017 | S. 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 |
| |
018 | B. Limketkai, L. Liao, D. Fox (all University of Washington) |
| Relational Object Maps for Mobile Robots |
| |
021 | Sumit Chopra, Raia Hadsell, Yann LeCun (Courant Institute, NYU) |
| Learning a Similarity Metric Discriminatively, with Application to Face Verification |
| |
023 | C.Alippi (Politecnico di Milano), D.Cogliati (Politecnico di Milano) |
| ACTIVE NOISE CONTROL: COMPENSATING NON-STATIONARY ACOUSTIC SIGNALS |
| |
024 | F. Fleuret (EPFL), W. Gerstner (EPFL) |
| A Bayesian Kernel for the Prediction of Neuron Properties from Binary Gene Profiles |
| |
026 | C. Alippi (Politecnico di Milano), D. Cogliati (Politecnico di Milano), C.Galperti (Politecnico di Milano), E. Pasero (Politecnico di Torino) |
| A FIRST STEP TOWARDS THE STATE OF SNOW CLASSIFICATION |
| |
032 | A. Goulon (ESPCI, Paris), A. Duprat (ESPCI, Paris), G. Dreyfus (ESPCI, Paris) |
| Graph machines |
| |
033 | C. Garcia (France Telecom division R&D) |
| A Connexionnist Approach for Robust and Precise Facial Feature Detection in Complex Scenes |
| |
035 | A. Kapoor (MIT), and Yuan (Alan) Qi (MIT), and Rosalind W. Picard (MIT) |
| Bayesian Semi-Supervised Classification |
| |
037 | W. Dong, M. Martin, and A. Pentland (MIT) |
| Using the Influence Model to Capture Group Interactions |
| |
038 | Tulay Adali (University of Maryland Baltimore County) |
| Signal Processing with Complex Nonlinearities |
| |
039 | C. Dima and M. Hebert (CMU) |
| Pool-based Active Learning with Data Block |
| |
040 | S. Hochreiter (TU Berlin), and K. Obermayer (TU Berlin) |
| Sequence Classification For Protein Analysis |
| |
041 | Lawrence Carin, Nilanjan Dasgupta, Shaorong Chang, Yuting Qi (Duke University) |
| Variational Bayes and Expectation Propagation for Unsupervised Feature Selection, Clustering and Density Estimation |
| |
045 | Y. Bengio (U. Montreal) and H. Larochelle (U. Montreal) |
| Non-Local Manifold Parzen Windows |
| |
046 | N. Le Roux (U. de Montreal), Y. Bengio (U. de Montreal) and R. Ducharme (U. de Montreal) |
| Combining density estimators to improve classification performance |
| |
048 | John Kaufhold, Pascale Rondot, Roderic Collins, and Anthony Hoogs (all from GE Research) |
| Multiclass Boosting on Region Graphs Applied to Aerial Video Content Recognition |
| |
053 | Andrew I. Schein (U. Pennsylvania) and Lyle H. Ungar (U. Pennsylvania) |
| Active Learning for Multi-Class Logistic Regression |
| |
054 | A. Fraser, N. Hengartner, K. Vixie and B. Wohlberg (Los Alamos National Laboratory) |
| Exploiting Invariants for Classification with Application to Face Recognition |
| |
055 | N. Efron (Tel-Aviv U), and N. Intrator (Tel-Aviv U.) |
| Stabilizing Methods for Ill-Conditioned LDA, with Applications to Gene Expression Data |
| |
057 | D. 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 |
| |
066 | R. C. Venkatesan (Systems Research Corporation) |
| ICA through a Fisher game |
| |
067 | Vasin Punyakanok, Dan Roth, Wen-tau Yih, Dav Zimak (University of Illinois, Urbana) |
| Learning and Inference over Constrained Output |
| |
069 | Milind Mahajan (Microsoft Research), and Asela Gunawardana (Microsoft Research) |
| Phone classification using hidden conditional random fields |
| |
070 | G. 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 |
| |
072 | Tina Eliassi-Rad (Lawrence Livermore National Laboratory) and Terence Critchlow (Lawrence Livermore National Laboratory) |
| Similarity in Computational Sciences |
| |
073 | T. Ould Bachir (Ecole Polytechnique de Montreal), J.-J. Brault (Ecole Polytechnique de Montreal) |
| A Multiplexer-based Device for Simulated Binary Bayesian Networks |
| |
074 | M. Belkin, P. Niyogi, University of Chicago |
| On Graph and Manifold Laplacians: Towards a Theoretical Foundation |
| |
079 | Pierre-Alexandre Fournier and Jean-Jules Brault (Ecole Polytechnique de Montreal) |
| Learning the timbre of individuals for realistic speech synthesis |
| |
081 | Shantanu Chakrabartty ( Michigan State University ) and Gert Cauwenberghs ( Johns Hopkins University) |
| Sequence Learning and Decoding in Margin Propagation Networks |
| |
082 | V. de Sa (UCSD) |
| A Spectral Minimizing-Disagreement Algorithm |
| |
083 | R. C. Venkatesan (Systems Research Corporation) |
| Quantum clustering through a Fisher game |
| |
084 | John Langford (TTI Chicago) and Alina Beygelzimer (IBM Watson Research) |
| Sensitive Error Correcting Output Codes |
| |
087 | Martial Hue (Ecole des Mines de Paris, France), Jean-Philippe Vert (Ecole des Mines de Paris, France) |
| Semi-Supervised Ranking, and application to bioinformatics |
| |
090 | Srinivas Bangalore and Patrick Haffner (AT&T Labs-Research) |
| Classification of very large label sets |
| |
092 | Sung-eok Jeon and Chuanyi Ji, Georgia Tech |
| Graphical Models for Self-Configuration of Ad-hoc Wireless Networks |
| |
093 | Y. Jing (Georgia Tech), V. Pavlovic (Rutgers), J. M. Rehg (Georgia Tech) |
| Discriminative Learning Using Boosted Generative Models |
| |
094 | Jan Eichhorn and Olivier Chapelle |
| Image Categorization with Support Vector Machines: Kernels for Local Image Descriptors |
| |
095 | W. Kim (Georgia Tech), N. Jojic (Microsoft Research), and J. M. Rehg (Georgia Tech) |
| Epitomic Analysis of Human Motion |
| |
096 | Y. Altun and D. McAllester (TTI-C) |
| Semi-Supervised Structure Learning |
| |
098 | T. Breuel (U. Kaiserslautern and DFKI) |
| Approximate vs. Representative Nearest Neighbors |
| |
099 | Valery A. Petrushin (Accenture Technology Labs) |
| Mining Events in Multi-camera Surveillance Video using Self-organizing Maps |
| |