Papers
Learning Graphs with a Few Hubs
Rashish Tandon, Pradeep Ravikumar
Large-scale Multi-label Learning with Missing Labels
Hsiang-Fu Yu, Prateek Jain, Purushottam Kar et al.
Provable Bounds for Learning Some Deep Representations
Sanjeev Arora, Aditya Bhaskara, Rong Ge et al.
Nuclear Norm Minimization via Active Subspace Selection
Cho-Jui Hsieh, Peder Olsen
A Divide-and-Conquer Solver for Kernel Support Vector Machines
Cho-Jui Hsieh, Si Si, Inderjit Dhillon
Densifying One Permutation Hashing via Rotation for Fast Near Neighbor Search
Anshumali Shrivastava, Ping Li
Coordinate-descent for learning orthogonal matrices through Givens rotations
Uri Shalit, Gal Chechik
Asymptotically consistent estimation of the number of change points in highly dependent time series
Azadeh Khaleghi, Daniil Ryabko
Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection
Arun Iyer, Saketha Nath, Sunita Sarawagi
Unimodal Bandits: Regret Lower Bounds and Optimal Algorithms
Richard Combes, Alexandre Proutiere
Online Learning in Markov Decision Processes with Changing Cost Sequences
Travis Dick, Andras Gyorgy, Csaba Szepesvari
Forward-Backward Greedy Algorithms for General Convex Smooth Functions over A Cardinality Constraint
Ji Liu, Jieping Ye, Ryohei Fujimaki
Discriminative Features via Generalized Eigenvectors
Nikos Karampatziakis, Paul Mineiro
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels
Jiyan Yang, Vikas Sindhwani, Haim Avron et al.
(Near) Dimension Independent Risk Bounds for Differentially Private Learning
Prateek Jain, Abhradeep Guha Thakurta
A Deep and Tractable Density Estimator
Benigno Uria, Iain Murray, Hugo Larochelle
On Modelling Non-linear Topical Dependencies
Zhixing Li, Siqiang Wen, Juanzi Li et al.
Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning
François Denis, Mattias Gybels, Amaury Habrard
Bias in Natural Actor-Critic Algorithms
Philip Thomas
On Measure Concentration of Random Maximum A-Posteriori Perturbations
Francesco Orabona, Tamir Hazan, Anand Sarwate et al.
Condensed Filter Tree for Cost-Sensitive Multi-Label Classification
Chun-Liang Li, Hsuan-Tien Lin
Diagnosis determination: decision trees optimizing simultaneously worst and expected testing cost
Ferdinando Cicalese, Eduardo Laber, Aline Medeiros Saettler
Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach
Rémi Bardenet, Arnaud Doucet, Chris Holmes
Modeling Correlated Arrival Events with Latent Semi-Markov Processes
Wenzhao Lian, Vinayak Rao, Brian Eriksson et al.
Deterministic Policy Gradient Algorithms
David Silver, Guy Lever, Nicolas Heess et al.