Papers
Hamiltonian Monte Carlo Without Detailed Balance
Jascha Sohl-Dickstein, Mayur Mudigonda, Michael DeWeese
Learning Sum-Product Networks with Direct and Indirect Variable Interactions
Amirmohammad Rooshenas, Daniel Lowd
Memory Efficient Kernel Approximation
Si Si, Cho-Jui Hsieh, Inderjit Dhillon
True Online TD(lambda)
Harm Seijen, Rich Sutton
Admixture of Poisson MRFs: A Topic Model with Word Dependencies
David Inouye, Pradeep Ravikumar, Inderjit Dhillon
Coherent Matrix Completion
Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi et al.
Narrowing the Gap: Random Forests In Theory and In Practice
Misha Denil, David Matheson, Nando De Freitas
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
Jeff Donahue, Yangqing Jia, Oriol Vinyals et al.
Efficient Continuous-Time Markov Chain Estimation
Monir Hajiaghayi, Bonnie Kirkpatrick, Liangliang Wang et al.
Spherical Hamiltonian Monte Carlo for Constrained Target Distributions
Shiwei Lan, Bo Zhou, Babak Shahbaba
Towards an optimal stochastic alternating direction method of multipliers
Samaneh Azadi, Suvrit Sra
Agnostic Bayesian Learning of Ensembles
Alexandre Lacoste, Mario Marchand, François Laviolette et al.
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