| 005 | Ahmad Emami and Frederick Jelinek, CLSP, Johns Hopkins University |
| A Neural Syntactic Language Model |
| |
| 007 | Eric B. Baum |
| What is Thought? |
| |
| 010 | John Lafferty, Yan Liu, and Xiaojin Zhu (Carnegie Mellon University) |
| Kernel Conditional Random Fields: Representation, Clique Selection, and Semi-Supervised Learning |
| |
| 011 | Bill Triggs and Ankur Agarwal (GRAVIR-CNRS-INRIA, Grenoble, France) |
| Learning to Reconstruct 3D Human Pose and Motion from Silhouettes |
| |
| 015 | Y. Lin, D. D. Lee, and L. K. Saul (U. Pennsylvania) |
| Generative Models for Auditory Localization |
| |
| 021 | M. Paskin (U. California, Berkeley), and C. Guestrin (Intel Berkeley Research Center) |
| Distributed Inference in Sensor Networks |
| |
| 023 | S. Lazebnik (Beckman Institute, U. Illinois), C. Schmid (INRIA, Rhone-Alpes), and J. Ponce (Beckman Institute, U. Illinois) |
| Learning Local Affine-Invariant Part Representations for Object Recognition |
| |
| 024 | H.J. Kappen and J. Mooij (University of Nijmegen) |
| Validity estimates for belief propagation on real-world networks |
| |
| 025 | D. Heckerman, C. Meek (Microsoft), and D. Koller (Stanford) |
| Probabilistic Models for Relational Data |
| |
| 036 | R. Collobert (IDIAP), and S. Bengio (IDIAP) |
| MLP = (SVM)^2 |
| |
| 041 | S. Kumar (CMU), and M. Hebert (CMU) |
| Multiclass Discriminative Random Fields for Object Detection |
| |
| 043 | Fu Jie Huang (Courant Institute, NYU), Yann LeCun (Courant Institute, NYU), Leon Bottou (NEC) |
| Learning to Recognize Object Categories with Invariance Pose, Illumination, and Clutter |
| |
| 047 | Y.W. Teh (UC Berkeley), M.I. Jordan (UC Berkeley), M.J. Beal (U Toronto), D.M. Blei (UC Berkeley) |
| Hierarchical Dirichlet Processes |
| |
| 048 | J. Goldstein, J.C. Platt, C.J.C. Burges (Microsoft Research) |
| Redundant Bit Vectors for Searching High-Dimensional Regions |
| |
| 051 | D. Anguelov (Stanford U), D. Koller (Stanford U), P. Srinivasan (Stanford U), S. Thrun (Stanford U), H. Pang (Stanford U) and J. Davis(Honda Research Institute) |
| The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces |
| |
| 054 | R. Tedrake (MIT), T.W. Zhang (MIT), M. Fong (MIT), and H.S. Seung (MIT & Howard Hughes) |
| Learning to Walk by Actuating a Passive Dynamic Walker |
| |
| 055 | Ben Taskar (Stanford), and Vassil Chatalbashev (Stanford), and Daphne Koller (Stanford) |
| Associative Markov Networks |
| |
| 062 | A. Cutler (Utah State U.) Leo Breiman (UC Berkeley) |
| Visualizing Random Forests |
| |
| 063 | Yann LeCun (Courant Institute, NYU), Eric Cosatto, Jan Ben, Urs Muller, Beat Flepp (Net-Scale Technologies) |
| End-to-End Learning of Vision-Based Obstacle Avoidance for Off-Road Robots |
| |
| 065 | N. Jojic, V. Jojic, D. Heckerman, C. Meek (Microsoft Research) |
| Graphical models for rational design of AIDS vaccine cocktails |
| |
| 071 | Trevor Hastie (Stanford U), Saharon Rosset (IBM, Yorktown) and Ji Zhu (U. Michigan) |
| The Entire Regularization Path for the Support Vector Machine |
| |
| 079 | Q. Morris (U. Toronto), B. Frey (U Toronto), O Shai (U Toronto) |
| Gene function prediction using mouse gene expression profiles |
| |
| 084 | B. J. Frey (University of Toronto) and N. Jojic (Microsoft Research) |
| Learning the "epitome" of an image |
| |
| 086 | Craig G. Nevill-Manning (Google) and Ian H. Witten (U Waikato, New Zealand) |
| Extracting Structured Data from Database-Backed Web Sites using Sequence Alignment |
| |
| 087 | Margarita Osadchy (NEC), Matthew Miller (NEC), Yann LeCun (Courant Institute, NYU) |
| Synergistic Face Detection and Pose Estimation |
| |
| 001 | J. Langford (TTI-Chicago) |
| The Method of Reduction in Machine Learning |
| |
| 002 | C.Alippi (Politecnico di Milano), and F.Scotti (University of Milan) |
| A Combination of Multiple Classifier Design for Low-Complex, Highly Performing and Power-Aware Classifiers |
| |
| 003 | A.Karatzoglou D. Meyer (U. Tech. Vienna) A.Zeileis K.Hornik (B. U. Vienna) |
| kernlab - A kernel methods package for R |
| |
| 004 | J. Kaufhold (GE Global Research Center), and A. Hoogs (GE Global Research Center) |
| Learning to Segment Images Using Region-Based Perceptual Edge Features |
| |
| 006 | C. Raphael |
| Musical Score Following with Latent Tempo Variables |
| |
| 008 | R. Kozma (U. Memphis), W.J. Freeman (UC Berkeley), P.Erdi (Kalamazoo & KFKI Hungary) |
| Learning in the KIV Dynamic Neural Network Model of the Cortico-Hippocampal Formation: Biological Basis and Computational Applications |
| |
| 009 | Sumit Basu (Microsoft Research), and Tanzeem Choudhury (Intel Research) |
| Learning Relationships from Conversational Patterns |
| |
| 012 | M. Embrechts (Rensselaer Polytechnic Institute) |
| Direct Kernel Methods for Molecular Design: Kernel Centering, Feature Selection and Regularization |
| |
| 013 | V. Jojic (Microsoft Research), N. Jojic (Microsoft Research), C. Meek (Microsoft Research), D. Geiger (Technion, Israel), A. Siepel (UC Santa Cruz.), D. Haussler (UC Santa Cruz.), D. Heckerman (Microsoft Research) |
| Efficient Approximations for Learning Phylogenetic HMM Models from Data |
| |
| 014 | Ciprian Chelba (Microsoft Research) and Alex Acero (Microsoft Research) |
| Conditional Maximum Likelihood Estimation using Rational Function Growth Transform |
| |
| 016 | S. Akaho (AIST) |
| The e-PCA and m-PCA: Dimension Reduction by Information Geometry |
| |
| 017 | P. Haffner (AT&T labs-research) |
| An equivalence between the thermometer representation of |
| |
| 026 | Lyle Ungar, Dean Foster and Bob Stine (U. of Pennsylvania) |
| Streaming Feature Selection |
| |
| 027 | V. Petrushin (Accenture Technology Labs) |
| Adaptive Algorithm for Pitch-synchronous Speech Signal Segmentation |
| |
| 029 | N. Intrator (Brown U) and N. Neretti (Brown U) and Leon N Cooper |
| Robust Statistics from multiple pings improves noise tolerance in sonar |
| |
| 030 | M. Seeger (U. California, Berkeley), and M. I. Jordan (U. California, Berkeley) |
| Fast Sparse Gaussian Process Classification with Multiple Classes |
| |
| 032 | S. Matwin (Univ. of Ottawa), E. Alphonse (INRA - France), N. Stroppa (ENST - France) |
| Relational Feature Selection |
| |
| 034 | S. Lenser (CMU) and M. Veloso (CMU) |
| Time Series Classification Using Non-Parametric Statistics |
| |
| 035 | B. Upcroft (U. Sydney), S. Kumar (U. Sydney), H. Durrant-Whyte (U. Sydney) |
| Unsupervised Data Association in Unstructured Outdoor Environments |
| |
| 037 | H. Guo, A. Rangarajan (U. Florida), S. Joshi (UNC Chapel Hill) and L. Younes (Johns Hopkins) |
| Diffeomorphic point matching for statistical shape analysis |
| |
| 038 | Y. Oussar (ESPCI), G. Dreyfus (ESPCI) |
| Generalized leverages and generalization error |
| |
| 039 | Jianxin Wu (Georgia Tech), Matthew D. Mullin (Georgia Tech), James M. Rehg (Georgia Tech) |
| Linear Programming Ensemble for Classifiers with Highly |
| |
| 040 | R. Kondor (Columbia), T. Jebara (Columbia), G. Csanyi (U. Cambridge), E. Ahnert (U. Cambridge) |
| Learning from Derivatives and other Linear functionals |
| |
| 042 | Y. Bengio (U. Montreal), O. Delalleau (U. Montreal), N. LeRoux (U. Montreal) |
| Non-parametric function induction in semi-supervised learning |
| |
| 044 | A. Banerjee (U. Texas at Austin), I. Dhillon (U. Texas at Austin), J. Ghosh (U. Texas at Austin), S. Merugu (U. Texas at Austin) |
| Rate Distortion, Bregman Divergences and Maximum Likelihood Mixture Estimation |
| |
| 045 | S. Roweis (U. Toronto) |
| Nonlinear Sensor Fusion Networks |
| |
| 046 | Joydeep Ghosh (U. Texas), Suju Rajan (U.Texas) and Melba Crawford (U. Texas/Center for Space Res.) |
| Automatic Generation of Class Hierarchies for High-Dimensional Multiclass Problems |
| |
| 049 | D. Ross (U. Toronto), J. Lim (U of Illinois), and M.-H. Yang (Honda Research Institute) |
| Adaptive Probablistic Visual Tracking with Incremental Subspace Upldat |
| |
| 052 | T. Jebara (Columbia University) and Y. Bengio (Universite de Montreal) |
| Orbit Learning using Convex Optimization |
| |
| 053 | Austin I. Eliazar and Ronald Parr |
| Learning Probabilistic Robot Motion Models |
| |
| 056 | R. Caruana (Cornell), and A. Niculescu-Mizil (Cornell) |
| An Empirical Comparison of Supervised Learning Methods Using Nine Performance Criteria |
| |
| 059 | B. Kegl, L. Wang (University of Montreal) |
| Adaptive regularization of base classifiers in boosting |
| |
| 061 | O. Madani and D. M. Pennock and G. W. Flake (Yahoo! Research Labs) |
| Co-Validation: Using Model Disagreement on Unlabeled Data for Estimating Prediction Error and Variance |
| |
| 064 | Greg Grudic (University of Colorado at Boulder) |
| Basis Function Regression and Classification Models with Probabilistic Predictions |
| |
| 068 | M. Reyes-Gomez (Columbia University), N. Jojic (Microsoft Research) and D.P.W. Ellis (Columbia University) |
| Detailed graphical models for source separataion and missing data interpolation in audio |
| |
| 070 | J. Lim (U of Illinois), J. Ho (UCSD), M-H Yang (Honda Research Institute), K-L Lee (UIUC), David Kriegman (UCSD) |
| Image Clustering wiht Metric, Local Linear Structure and Affine Symmetry |
| |
| 072 | S.C. Kremer (U. Guelph) |
| Stochastic Correlative Learning Algorithms for Recurrent Network Learning |
| |
| 074 | M. Alex O. Vasilescu and Demetri Terzopoulos, NYU, UofT |
| Multilinear Independent Components Analysis |
| |
| 075 | M.J. Beal (U Toronto), Y.W. Teh (UC Berkeley), and M.I. Jordan (UC Berkeley) |
| Infinite Hidden Markov Models via the Hierarchical Dirichlet Process |
| |
| 076 | A. Silvescu (Iowa State U.), and V. Honavar (Iowa State U.) |
| A Graphical Model for Shallow Parsing Sequences |
| |
| 078 | M. Oresic (VTT Biotechnology) |
| Characterization of physiological states using metabolic profiling approaches |
| |
| 080 | J. Moody, Y. Liu, (International Computer Science Institute), M. Saffell and K. Youn (OGI School of Science and Engineering) |
| Stochastic Direct Reinforcement: Representations, Recurrence and Stochastic Games |
| |
| 081 | H. Attias (HT Attias Inc) and Matthew J. Beal (U. Toronto) |
| Tree of Latent Mixtures for Bayesian Modelling and Classification of High Dimensional Data |
| |
| 082 | S. Nagarajan (UCSF), M. Sahani (UCSF), H. Attias (HT Attias Inc) |
| A Graphical Model for Electromagnetic Source Imaging |
| |
| 083 | Sara C. Madeira (UBI, Portugal) and Arlindo L. Oliveira (IST/INESC-ID, Portugal) |
| Biclustering Algorithms for Biological Data Analysis |
| |
| 089 | E. Glover (NEC-Labs), B. Klock (NEC-Labs), D. Berton (NEC-Labs) |
| Building a Personalizable Genre-Based Metasearch Engine that is Easy to Train |
| |
