Papers
4,025 papers found
Efficient Bregman Projections onto the Permutahedron and Related Polytopes
Cong Han Lim, Stephen J. Wright
Efficient Sampling for k-Determinantal Point Processes
Chengtao Li, Stefanie Jegelka, Suvrit Sra
Enumerating Equivalence Classes of Bayesian Networks using EC Graphs
Eunice Yuh-Jie Chen, Arthur Choi Choi, Adnan Darwiche
Exponential Stochastic Cellular Automata for Massively Parallel Inference
Manzil Zaheer, Michael Wick, Jean-Baptiste Tristan et al.
Fast and Scalable Structural SVM with Slack Rescaling
Heejin Choi, Ofer Meshi, Nathan Srebro
Fast Convergence of Online Pairwise Learning Algorithms
Martin Boissier, Siwei Lyu, Yiming Ying et al.
Fast Dictionary Learning with a Smoothed Wasserstein Loss
Antoine Rolet, Marco Cuturi, Gabriel Peyré
Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with Ordered L1-Norm
Sangkyun Lee, Damian Brzyski, Malgorzata Bogdan
Fitting Spectral Decay with the k-Support Norm
Andrew McDonald, Massimiliano Pontil, Dimitris Stamos
Generalized Ideal Parent (GIP): Discovering non-Gaussian Hidden Variables
Yaniv Tenzer, Gal Elidan
Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and Tree
Chen-Yu Lee, Patrick W. Gallagher, Zhuowen Tu
Geometry Aware Mappings for High Dimensional Sparse Factors
Avradeep Bhowmik, Nathan Liu, Erheng Zhong et al.
GLASSES: Relieving The Myopia Of Bayesian Optimisation
Javier Gonzalez, Michael Osborne, Neil Lawrence
Global Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation
Dejiao Zhang, Laura Balzano
Globally Sparse Probabilistic PCA
Pierre-Alexandre Mattei, Charles Bouveyron, Pierre Latouche
Graph Connectivity in Noisy Sparse Subspace Clustering
Yining Wang, Yu-Xiang Wang, Aarti Singh
Graph Sparsification Approaches for Laplacian Smoothing
Veeru Sadhanala, Yu-Xiang Wang, Ryan Tibshirani
High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models
Chun-Liang Li, Kirthevasan Kandasamy, Barnabas Poczos et al.
How to Learn a Graph from Smooth Signals
Vassilis Kalofolias
Improper Deep Kernels
Uri Heinemann, Roi Livni, Elad Eban et al.
Improved Learning Complexity in Combinatorial Pure Exploration Bandits
Victor Gabillon, Alessandro Lazaric, Mohammad Ghavamzadeh et al.
Inference for High-dimensional Exponential Family Graphical Models
Jialei Wang, Mladen Kolar
Inverse Reinforcement Learning with Simultaneous Estimation of Rewards and Dynamics
Michael Herman, Tobias Gindele, Jörg Wagner et al.
K2-ABC: Approximate Bayesian Computation with Kernel Embeddings
Mijung Park, Wittawat Jitkrittum, Dino Sejdinovic
Large Scale Distributed Semi-Supervised Learning Using Streaming Approximation
Sujith Ravi, Qiming Diao