Papers
4,025 papers found
Bayesian Nonparametric Kernel-Learning
Junier B. Oliva, Avinava Dubey, Andrew G. Wilson et al.
Bayes-Optimal Effort Allocation in Crowdsourcing: Bounds and Index Policies
Weici Hu, Peter Frazier
Bethe Learning of Graphical Models via MAP Decoding
Kui Tang, Nicholas Ruozzi, David Belanger et al.
Bipartite Correlation Clustering: Maximizing Agreements
Megasthenis Asteris, Anastasios Kyrillidis, Dimitris Papailiopoulos et al.
Black-Box Policy Search with Probabilistic Programs
Jan-Willem Vandemeent, Brooks Paige, David Tolpin et al.
Breaking Sticks and Ambiguities with Adaptive Skip-gram
Sergey Bartunov, Dmitry Kondrashkin, Anton Osokin et al.
Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization
Changyou Chen, David Carlson, Zhe Gan et al.
C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching
Daniel Ritchie, Andreas Stuhlmüller, Noah Goodman
Chained Gaussian Processes
Alan D. Saul, James Hensman, Aki Vehtari et al.
Clamping Improves TRW and Mean Field Approximations
Adrian Weller, Justin Domke
Communication Efficient Distributed Agnostic Boosting
Shang-Tse Chen, Maria-Florina Balcan, Duen Horng Chau
Computationally Efficient Bayesian Learning of Gaussian Process State Space Models
Andreas Svensson, Arno Solin, Simo Särkkä et al.
Consistently Estimating Markov Chains with Noisy Aggregate Data
Garrett Bernstein, Daniel Sheldon
Control Functionals for Quasi-Monte Carlo Integration
Chris Oates, Mark Girolami
Controlling Bias in Adaptive Data Analysis Using Information Theory
Daniel Russo, James Zou
Convex Block-sparse Linear Regression with Expanders – Provably
Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad et al.
CRAFT: ClusteR-specific Assorted Feature selecTion
Vikas K. Garg, Cynthia Rudin, Tommi Jaakkola
Cut Pursuit: Fast Algorithms to Learn Piecewise Constant Functions
Loic Landrieu, Guillaume Obozinski
Deep Kernel Learning
Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov et al.
Determinantal Regularization for Ensemble Variable Selection
Veronika Rockova, Gemma Moran, Edward George
Discriminative Structure Learning of Arithmetic Circuits
Amirmohammad Rooshenas, Daniel Lowd
Distributed Multi-Task Learning
Jialei Wang, Mladen Kolar, Nathan Srerbo
Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation
Søren Hauberg, Oren Freifeld, Anders Boesen Lindbo Larsen et al.
DUAL-LOCO: Distributing Statistical Estimation Using Random Projections
Christina Heinze, Brian McWilliams, Nicolai Meinshausen
Early Stopping as Nonparametric Variational Inference
David Duvenaud, Dougal Maclaurin, Ryan Adams