- Discriminative Learning and Visual Interactive Behavior
- Structured Prediction Models for Chord Transcription of Music Audio Adrian Weller, Daniel Ellis, Tony Jebara
- 3D POSE ESTIMATION AND NORMALIZATION FOR FACE RECOGNITION
- Augmented Realities Integrating User and Physical Models
- Kernelizing Sorting, Permutation and Alignment for Minimum Volume PCA
- Bayesian OutTrees Tony Jebara
- Permutation Invariant SVMs Pannagadatta K. Shivaswamy pannaga@cs.columbia.edu
- Journal of Machine Learning Research 5 (2004) 819--844 Submitted 1/04; Published 7/04 Probability Product Kernels
- Bayesian inference, entropy, and the multinomial distribution Thomas P. Minka
- Regression by linear combination of basis Risi Kondor
- Clustered Blockwise PCA for Representing Visual Data
- Discriminative, Generative and Imitative Tony Jebara
- MIT Media Laboratory, Perceptual Computing Technical Report #440 Appears in: Proceedings of ICCV'98, Bombay, India, January 47, 1998
- Density Estimation under Independent Similarly Distributed Sampling Assumptions
- MultiTask Feature and Kernel Selection for SVMs Tony Jebara jebara@cs.columbia.edu
- Multiobject tracking with representations of the symmetric group Risi Kondor, Andrew Howard and Tony Jebara
- Orbit Learning using Convex Optimization Tony Jebara
- Sensory Augmented Computing: Wearing the Museum's Guide
- Ellipsoidal Kernel Machines Pannagadatta K. Shivaswamy
- Tracking Conversational Context for Machine Mediation of Human Discourse
- ActionReaction Learning: Analysis and Synthesis of Human
- Empirical Bernstein Boosting Pannagadatta K. Shivaswamy Tony Jebara
- Semi-Supervised Learning Graph Sparsification Graph Weighting Graph Labeling Experiments Conclusions Graph Construction and b-Matching for
- Bayesian Out-Trees Tony Jebara
- Fast b-Matching via Sufficient Selection Belief Propagation Bert Huang Tony Jebara
- MIT Media Laboratory, Perceptual Computing Technical Report #401 Submitted to CVPR November 1996
- An Interactive Computer Vision System DyPERS: Dynamic Personal Enhanced Reality System
- On Reversing Jensen's Inequality Tony Jebara
- Images as Bags of Pixels Tony Jebara
- Statistical Imitative Learning from Perceptual Data Tony Jebara Alex Pentland
- A Kernel Between Sets of Vectors Risi Kondor risi@cs.columbia.edu
- A short review of fundamental concepts from linear algebra January 27, 2004
- Feature Selection and Dualities in Maximum Entropy Discrimination
- Bhattacharyya and Expected Likelihood Kernels Tony Jebara and Risi Kondor
- Dynamical Systems Trees Andrew Howard
- Appears In: Advances in Neural Information Processing Systems 11, MIT Press, 1999. Bayesian Modeling of Facial Similarity
- Gaussian and Wishart Hyperkernels Risi Kondor, Tony Jebara
- Kernelizing the Minimum Volume Ellipsoid October 1, 2007
- Inferring a Gaussian distribution Thomas P. Minka
- Learning Monotonic Transformations for Classification
- Convex Invariance Learning Tony Jebara
- Action-Reaction Learning: Analysis and Synthesis of Human
- Learning a Kernel Matrix for Nonlinear Dimensionality Reduction Kilian Q. Weinberger kilianw@cis.upenn.edu
- Journal of Machine Learning Research 5 (2004) 819844 Submitted 1/04; Published 7/04 Probability Product Kernels
- Density Estimation under Independent Similarly Distributed Sampling Assumptions
- Tracking Conversational Context for Machine Mediation of Human Discourse
- Margin Constrints MED Feature & Kernel Sparsity Multi-Task Constraints SQP Relative Margin Conclusions Multi-Task Discriminative Estimation for
- B-Matching for Spectral Clustering Tony Jebara and Vlad Shchogolev
- A Kernel Between Sets of Vectors Risi Kondor risi@cs.columbia.edu
- 3D Structure from 2D Motion Tony Jebara, Ali Azarbayejani and Alex Pentland
- Exact Graph Structure Estimation with Degree Priors Bert Huang and Tony Jebara
- Collaborative Filtering via Rating Concentration Bert Huang Tony Jebara
- Graph Transduction via Alternating Minimization Jun Wang jwang@ee.columbia.edu
- CitySenseTM : multiscale space time clustering of
- S n ob : a C++ toolkit for fast Fourier transforms on the symmetric Development version (unstable)
- Sensory Augmented Computing: Wearing the Museum's Guide
- MAP Estimation, Message Passing, and Perfect Graphs Tony Jebara
- Loopy Belief Propagation for Bipartite Maximum Weight b-Matching Computer Science Dept.
- Learning from Out-Tree Dependent Data Tony Jebara, Columbia University, jebara@cs.columbia.edu
- Structure Preserving Embedding Blake Shaw blake@cs.columbia.edu
- MIT Media Laboratory, Perceptual Computing Technical Report #463 DyPERS: Dynamic Personal Enhanced Reality System
- Statistical Imitative Learning from Perceptual Data Tony Jebara
- Background Matchings Perfect Graphs MAP Estimation MAP Estimation, Message Passing and Perfect
- Vol. 22 no. 22 2006, pages 27532760 doi:10.1093/bioinformatics/btl475BIOINFORMATICS ORIGINAL PAPER
- 3D POSE ESTIMATION AND NORMALIZATION FOR FACE RECOGNITION
- Maximum Conditional Likelihood via Bound Maximization and the CEM
- Loopy Belief Propagation for Bipartite Maximum Weight
- Out-Tree Dependent Nonparametric Bayesian Inference Tony Jebara jebara@cs.columbia.edu
- On Reversing Jensen's Inequality Tony Jebara
- Convex Invariance Learning Tony Jebara
- Laplacian Spectrum Learning Pannagadatta K. Shivaswamy and Tony Jebara
- Pannaga Shivaswamy Tony Jebara
- Graphical Modeling and Inference with Perfect Graphs Tony Jebara
- Structured Prediction with Relative Margin Pannagadatta Shivaswamy and Tony Jebara
- Dimensionality Reduction, Clustering, and PlaceRank Applied to Spatiotemporal Flow Data
- Relative Margin Machines Pannagadatta K Shivaswamy and Tony Jebara
- Visualizing Graphs with Structure Preserving Department of Computer Science
- Minimum Volume Embedding Computer Science Dept.
- Ellipsoidal Kernel Machines Pannagadatta K. Shivaswamy
- Multi-object tracking with representations of the symmetric group Risi Kondor, Andrew Howard and Tony Jebara
- Spectral Clustering and Embedding with Hidden Markov Models
- Permutation Invariant SVMs Pannagadatta K. Shivaswamy pannaga@cs.columbia.edu
- B-Matching for Embedding Tony Jebara, Blake Shaw, and Vlad Shchogolev
- Square Root Propagation Andrew G. Howard
- Dynamical Systems Trees Andrew Howard
- Multi-Task Feature and Kernel Selection for SVMs Tony Jebara jebara@cs.columbia.edu
- An SVM Learning Approach to Robotic Grasping Raphael Pelossof, Andrew Miller, Peter Allen, Tony Jebara
- Proceedings of the 2004 International Conference on Development and Learning
- Discriminative, Generative and Imitative Tony Jebara
- Feature Selection and Dualities in Maximum Entropy Discrimination
- Appears In: Advances in Neural Information Processing Systems 11, MIT Press, 1999. Bayesian Modeling of Facial Similarity
- MIT Media Laboratory, Perceptual Computing Technical Report #440 Appears in: Proceedings of ICCV'98, Bombay, India, January 4-7, 1998
- Mixtures of Eigenfeatures for Real-Time Structure
- Action Reaction Learning: Analysis and Synthesis of Human Tony Jebara Alex Pentland
- Augmented Realities Integrating User and Physical Models
- MIT Media Laboratory, Perceptual Computing Technical Report #439 Appears in: Proc. of the Intl. Symposium on Wearable Computers, Cambridge MA, Oct. 1997
- MIT Media Laboratory, Perceptual Computing Technical Report #401 Submitted to CVPR November 1996
- Journal of Machine Learning Research 12 (2011) 75-110 Submitted 4/09; Revised 10/10; Published 1/11 Multitask Sparsity via Maximum Entropy Discrimination
- EMPIRICAL INFERENCE SCIENCE Vladimir Vapnik
- Images as Bags of Pixels Tony Jebara
- Tony Jebara, Columbia University Advanced Machine
- Tony Jebara, Columbia University Advanced Machine
- Background Perfect Graphs MAP Estimation Graphical Modeling and Inference with
- Multimodal Person Recognition using Unconstrained Audio and Video
- Tony Jebara, Columbia University Advanced Machine
- Structured Network Learning Stuart Andrews
- Learning Regulatory Networks from Sparsely Sampled Time Series Expression Data
- Gaussian and Wishart Hyperkernels Risi Kondor, Tony Jebara
- Maximum Conditional Likelihood via Bound Maximization and the CEM
- Tony Jebara, Columbia University Advanced Machine
- Tony Jebara, Columbia University Advanced Machine
- Bayesian evidence kernel for linear
- Columbia University Learning and Empirical Inference Spring 2007
- , , 1{43 () c Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
- Tony Jebara, Columbia University Advanced Machine
- Tony Jebara, Columbia University Advanced Machine
- Optimizing Eigen-Gaps and Spectral Functions using Iterated SDP
- Learning Monotonic Transformations for Classification
- Tony Jebara, Columbia University Advanced Machine
- Feature Selection for SVMs , S. Mukherjee
- in Adv. in Neural Info. Proc. Systems, volume 9, MIT Press, 1997. Joshua B. Tenenbaum
- Transformation-Invariant Clustering and Dimensionality Reduction Using EM
- A Short Introduction to Hilbert Space Methods in Machine Learning
- Employing hidden Markov models of neural spike-trains toward the improved
- The " Netflix" Challenge Predicting User preferences using
- Introduction Spectral Clustering for one mic Audio Blind
- Structured prediction using the network perceptron
- Introduction Methodology
- Orbit Learning using Convex Optimization Tony Jebara
- Transformation Learning Via Kernel Alignment Andrew Howard and Tony Jebara
- Kernelizing the Minimum Volume Ellipsoid October 1, 2007
- Object Indexing using an Iconic Sparse Distributed Memory Rajesh P.N. Rao and Dana H. Ballard
- Bhattacharyya and Expected Likelihood Kernels Tony Jebara and Risi Kondor
- Action Reaction Learning: Automatic Visual Analysis and Synthesis of Interactive Behaviour
- Snob : a C++ toolkit for fast Fourier transforms on the symmetric Development version (unstable)
- Nonstationary kernel combination Darrin P. Lewis dplewis@cs.columbia.edu
- Tony Jebara, Columbia University Advanced Machine
- Alternating projection for independent component Michael Mandel
- 4 ( % 1 & 3 ' " ' ! . 2
- Time-frequency onset detection in music mixtures: building a ground truth dataset and first results
- Curriculum Vitae Tony Jebara, PhD, Associate Professor, Department of Computer Science, Columbia University
- LATEX sample document Risi Kondor
- The Perceptron The perceptron implements a binary classifier f : RD
- Document classification with the multinomial model Having numbered the words in English 1 to M, let Xi be the number of occur-
- Spectral Clustering of Time Series Data
- Background Perfect Graphs MAP Estimation Graphical Modeling and Machine Learning with
- Survey on Frequent Pattern Mining Bart Goethals
- Sampling form distributions Let f : R+
- Clustering Graph Partition O( n) via Spectral O(
- Document classi cation with the multinomial model Having numbered the words in English 1 to M , let X i be the number of occur-
- L A T E X sample document Risi Kondor
- Sampling form distributions ! R + be a probability density function on a
- The Perceptron The perceptron implements a binary classi er f : R D 7! f+1; 1g with a linear
- Variance Penalizing AdaBoost Pannagadatta K. Shivaswamy
- Learning a Distance Metric from a Network Computer Science Dept.
