Papers
572 papers found
Thompson Sampling and Approximate Inference
My Phan, Yasin Abbasi Yadkori, Justin Domke
Fourier Sparse Leverage Scores and Approximate Kernel Learning
Tamas Erdelyi, Cameron Musco, Christopher Musco
Learning to Approximate a Bregman Divergence
Ali Siahkamari, XIDE XIA, Venkatesh Saligrama et al.
On the Convergence of Smooth Regularized Approximate Value Iteration Schemes
Elena Smirnova, Elvis Dohmatob
A simple normative network approximates local non-Hebbian learning in the cortex
Siavash Golkar, David Lipshutz, Yanis Bahroun et al.
Approximate Heavily-Constrained Learning with Lagrange Multiplier Models
Harikrishna Narasimhan, Andrew Cotter, Yichen Zhou et al.
Approximate Cross-Validation for Structured Models
Soumya Ghosh, Will Stephenson, Tin D Nguyen et al.
Approximate Cross-Validation with Low-Rank Data in High Dimensions
Will Stephenson, Madeleine Udell, Tamara Broderick
Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms
Hilal Asi, John C. Duchi
On the Expressiveness of Approximate Inference in Bayesian Neural Networks
Andrew Foong, David Burt, Yingzhen Li et al.
Probably Approximately Correct Constrained Learning
Luiz Chamon, Alejandro Ribeiro
ImpatientCapsAndRuns: Approximately Optimal Algorithm Configuration from an Infinite Pool
Gellert Weisz, András György, Wei-I Lin et al.
Pipeline PSRO: A Scalable Approach for Finding Approximate Nash Equilibria in Large Games
Stephen Mcaleer, JB Lanier, Roy Fox et al.
Quantile Propagation for Wasserstein-Approximate Gaussian Processes
Rui Zhang, Christian Walder, Edwin V. Bonilla et al.
Minibatch Stochastic Approximate Proximal Point Methods
Hilal Asi, Karan Chadha, Gary Cheng et al.
Approximate Decomposable Submodular Function Minimization for Cardinality-Based Components
Nate Veldt, Austin R Benson, Jon M. Kleinberg
SPANN: Highly-efficient Billion-scale Approximate Nearest Neighborhood Search
Qi Chen, Bing Zhao, Haidong Wang et al.
A variational approximate posterior for the deep Wishart process
Sebastian Ober, Laurence Aitchison
Approximate optimization of convex functions with outlier noise
Anindya De, Sanjeev Khanna, Huan Li et al.
Leveraging Recursive Gumbel-Max Trick for Approximate Inference in Combinatorial Spaces
Kirill Struminsky, Artyom Gadetsky, Denis Rakitin et al.
Attention Approximates Sparse Distributed Memory
Trenton Bricken, Cengiz Pehlevan
Fast Approximate Dynamic Programming for Infinite-Horizon Markov Decision Processes
Mohamad Amin Sharifi Kolarijani, Gyula Max, Peyman Mohajerin Esfahani
Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm
Yasunori Akagi, Naoki Marumo, Hideaki Kim et al.