- New Approximation Algorithms for Minimum Enclosing Convex Ankan Saha # S.V. N. Vishwanathan + Xinhua Zhang #
- Accelerated Training of Conditional Random Fields with Stochastic Gradient Methods
- Journal of Machine Learning Research 8 (2007) Submitted 11/06; Published / Fast Iterative Kernel Principal Component Analysis
- Entropy Regularized LPBoost Manfred K. Warmuth1
- Semi-Markov Models for Sequence Segmentation Qinfeng Shi
- Learnability of Probabilistic Automata via Omri Guttman, S.V.N. Vishwanathan, and Robert C. Williamson
- New Approximation Algorithms for Minimum Enclosing Convex S.V. N. Vishwanathan
- Journal of Machine Learning Research 7 (2006) 705--732 Submitted 11/05; Published 05/06 Step Size Adaptation in Reproducing Kernel Hilbert Space
- Fast Computation of Graph Kernels # S.V. N. Vishwanathan
- DRAFT BinetCauchy Kernels S.V.N. Vishwanathan, Alexander J. Smola
- Fast and Space E#cient String Kernels using Su#x Arrays Choon Hui Teo choonhui.teo@rsise.anu.edu.au
- Jigsawing : A Method to Create Virtual Examples in OCR data
- Learning to Compress Images and Videos Li Cheng Li.Cheng@nicta.com.au
- HILBERT SPACE EMBEDDINGS IN DYNAMICAL SYSTEMS Alexander J. Smola and S.V.N. Vishwanathan
- Conditional Random Fields for Multiagent Reinforcement Learning Xinhua Zhang xinhua.zhang@anu.edu.au
- Journal of Machine Learning Research 8 (2007) Submitted 11/06; Published --/--Fast Iterative Kernel Principal Component Analysis
- Geometric SVM : A Fast and Intuitive SVM Algorithm S.V.N. Vishwanathan, M. Narasimha Murty
- ICML 2009 Tutorial Survey of Boosting
- Accelerated Training of Conditional Random Fields with Stochastic Gradient Methods
- Entropy Regularized LPBoost Manfred K. Warmuth 1 , Karen A. Glocer 1 and S.V.N Vishwanathan 2
- Multiple Kernel Learning and the SMO Algorithm S. V. N. Vishwanathan, Zhaonan Sun, Nawanol Theera-Ampornpunt
- Journal of Machine Learning Research 11 (2010) 157 Submitted 11/08; Revised 11/09; Published -/10 A Quasi-Newton Approach to Nonsmooth
- CVPR 2008 Submission #2171. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. Consistent Image Analogies using Semi-supervised Learning
- Efficient Graphlet Kernels for Large Graph Comparison State-of-the-art graph kernels do not scale
- Kernel Extrapolation S.V.N. Vishwanathan a Karsten M. Borgwardt b,#
- Learning to Compress Images and Videos Li Cheng Li.Cheng@nicta.com.au
- Journal of Machine Learning Research 11 (2009) xxxxxx Submitted 02/09; Published xx/09 Hash Kernels for Structured Data
- 2004/08/23 16:53 1 Fast Kernels for String and Tree Matching
- SemiMarkov Models for Sequence Segmentation Qinfeng Shi
- Kernel Methods for Missing Variables Alex J. Smola, S.V.N. Vishwanathan
- Fast Iterative Kernel PCA Nicol N. Schraudolph Simon Gunter S.V. N. Vishwanathan
- ICML 2009 tutorial Survey of Boosting
- STEP SIZE-ADAPTED ONLINE SUPPORT VECTOR LEARNING Alexandros Karatzoglou
- Leaving the Span Manfred K. Warmuth 1,# and S.V.N. Vishwanathan 2
- tLogistic Regression Nan Ding 2 , S.V. N. Vishwanathan 1,2
- Bundle Methods for Machine Learning Alexander J. Smola, S.V. N. Vishwanathan, Quoc V. Le
- 2004/08/23 16:52 1 Fast Kernels for String and Tree Matching
- Multitask Learning without Label Correspondences Novi Quadrianto1
- Journal of Machine Learning Research 1 (2009) 1-55 Submitted 01/09; Published 04/09 Bundle Methods for Regularized Risk Minimization
- LargeScale Multiclass Transduction Thomas G artner
- STEP SIZEADAPTED ONLINE SUPPORT VECTOR LEARNING Alexandros Karatzoglou
- A QuasiNewton Approach to Nonsmooth Convex Optimization We extend the wellknown BFGS quasi
- BinetCauchy Kernels on Dynamical Systems and its Application to the Analysis of Dynamic Scenes #
- A Scalable Modular Convex Solver for Regularized Risk Minimization
- Laplace Propagation Alex J. Smola, S.V.N. Vishwanathan
- t-Logistic Regression , S.V. N. Vishwanathan1,2
- Use of Multi-category Proximal SVM for Data Set Reduction
- Journal of Machine Learning Research 11 (2010) 145 Submitted 05/08; Published xx/10 Graph Kernels
- Journal of Machine Learning Research 10 (2009) 2615-2637 Submitted 2/09; Revised 8/09; Published 11/09 Hash Kernels for Structured Data
- Binet-Cauchy Kernels on Dynamical Systems and its Application to the Analysis of Dynamic Scenes
- Kernel Extrapolation S.V.N. Vishwanathan a
- Journal of Machine Learning Research 7 (2006) 705732 Submitted 11/05; Published 05/06 Step Size Adaptation in Reproducing Kernel Hilbert Space
- Kohonen's SOM with Cache S.V.N. Vishwanathan, M. Narasimha Murty 1
- Journal of Machine Learning Research 11 (2009) xxx-xxx Submitted 02/09; Published xx/09 Hash Kernels for Structured Data
- The Entire Quantile Path of a Risk-Agnostic SVM Classifier Canberra Research Laboratory, NICTA
- A Scalable Modular Convex Solver for Regularized Risk Minimization
- Conditional Random Fields for Multi-agent Reinforcement Learning Xinhua Zhang xinhua.zhang@anu.edu.au
- CLASS PREDICTION FROM TIME SERIES GENE EXPRESSION PROFILES
- Large-Scale Multiclass Transduction Thomas Gartner
- Fast Computation of Graph Kernels S.V. N. Vishwanathan
- Learnability of Probabilistic Automata via Omri Guttman, S.V.N. Vishwanathan, and Robert C. Williamson
- Binet-Cauchy Kernels S.V.N. Vishwanathan, Alexander J. Smola
- Fast Kernels for String and Tree Matching S. V. N. Vishwanathan
- SSVM : A Simple SVM Algorithm S.V.N. Vishwanathan, M. Narasimha Murty
- Use of Multi-category Proximal SVM for Data Set Reduction
- Lower Bounds on Rate of Convergence of Cutting Plane Methods
- Multiple Kernel Learning and the SMO Algorithm S. V. N. Vishwanathan, Zhaonan Sun, Nawanol TheeraAmpornpunt
- sLLE: Spherical Locally Linear Embedding with Applications to Tomography Purdue University
- Variable Metric Stochastic Approximation Theory We provide a variable metric stochastic ap-
- CLASS PREDICTION FROM TIME SERIES GENE EXPRESSION PROFILES
- CVPR 2008 Submission #2171. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. Consistent Image Analogies using Semisupervised Learning
- Fast and Space Efficient String Kernels using Suffix Arrays Choon Hui Teo choonhui.teo@rsise.anu.edu.au
- A Quasi-Newton Approach to Nonsmooth Convex Optimization We extend the well-known BFGS quasi-
- BIOINFORMATICS Vol. 00 no. 00 2005
- S.V.N. Vishwanathan vishy@axiom.anu.edu.au Machine Learning Program, National ICT for Australia, Canberra, ACT 0200, Australia
- Leaving the Span Manfred K. Warmuth1,
- Smoothing Multivariate Performance Measures Xinhua Zhang
- Pacific Graphics 2011 Jan Kautz, Tong-Yee Lee, and Ming C. Lin
- Mach Learn manuscript No. (will be inserted by the editor)
- Accelerated Training of Max-Margin Markov Networks with Kernels
- Fair and Balanced: Learning to Present News Stories Amr Ahmed #1 , Choon Hui Teo #1 , S.V. N. Vishwanathan 2 , Alex Smola 1
- Quilting Stochastic Kronecker Product Graphs to Generate Multiplicative Attribute Graphs
- tdivergence Based Approximate Inference Nan Ding 2 , S.V. N. Vishwanathan 1,2 , Yuan Qi 2,1
- Journal of Machine Learning Research 10 (2011) 155 Submitted 11/11; Published 11/11 Smoothing Multivariate Performance Measures
- Quilting Stochastic Kronecker Product Graphs to Generate Multiplicative Attribute Graphs
- Fair and Balanced: Learning to Present News Stories , Choon Hui Teo1
- t-divergence Based Approximate Inference , S.V. N. Vishwanathan1,2
- Journal of Machine Learning Research 10 (2011) 1-55 Submitted 11/11; Published 11/11 Smoothing Multivariate Performance Measures
