Learning Theory

Concentration in unbounded metric spaces and algorithmic stability ICML 2014 Condensed Filter Tree for Cost-Sensitive Multi-Label Classification ICML 2014 Consistency of weighted majority votes NeurIPS 2014 Deep Boosting ICML 2014 Deep Fisher Kernels - End to End Learning of the Fisher Kernel GMM Parameters CVPR 2014 Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning ICML 2014 Distribution-independent Reliable Learning COLT 2014 Do Deep Nets Really Need to be Deep? NeurIPS 2014 Efficient learning by implicit exploration in bandit problems with side observations NeurIPS 2014 Efficient Partial Monitoring with Prior Information NeurIPS 2014 Efficient Sampling for Learning Sparse Additive Models in High Dimensions NeurIPS 2014 Ensemble Methods for Structured Prediction ICML 2014 Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm ICML 2014 Exploiting easy data in online optimization NeurIPS 2014 Follow the Leader If You Can, Hedge If You Must JMLR 2014 Forward-Backward Greedy Algorithms for General Convex Smooth Functions over A Cardinality Constraint ICML 2014 From Stochastic Mixability to Fast Rates NeurIPS 2014 Fundamental Limits of Online and Distributed Algorithms for Statistical Learning and Estimation NeurIPS 2014 Generalized Exponential Concentration Inequality for Renyi Divergence Estimation ICML 2014 Hard-Margin Active Linear Regression ICML 2014 Hardness of parameter estimation in graphical models NeurIPS 2014 How hard is my MDP?" The distribution-norm to the rescue" NeurIPS 2014 How transferable are features in deep neural networks? NeurIPS 2014 Improved Bounds for Online Learning Over the Permutahedron and Other Ranking Polytopes AISTATS 2014 Information-Theoretic Characterization of Sparse Recovery AISTATS 2014