Papers
572 papers found
Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions
Daniel D. Johnson, Ayoub El Hanchi, Chris J. Maddison
Efficient Model Updates for Approximate Unlearning of Graph-Structured Data
Eli Chien, Chao Pan, Olgica Milenkovic
ISAAC Newton: Input-based Approximate Curvature for Newton's Method
Felix Petersen, Tobias Sutter, Christian Borgelt et al.
Approximate Nearest Neighbor Search through Modern Error-Correcting Codes
Noam Touitou, Nissim Halabi
Approximate Vanishing Ideal Computations at Scale
Elias Samuel Wirth, Hiroshi Kera, Sebastian Pokutta
Approximate Bayesian Inference with Stein Functional Variational Gradient Descent
Tobias Pielok, Bernd Bischl, David Rügamer
Robustifying State-space Models for Long Sequences via Approximate Diagonalization
Annan Yu, Arnur Nigmetov, Dmitriy Morozov et al.
Approximately Piecewise E(3) Equivariant Point Networks
Matan Atzmon, Jiahui Huang, Francis Williams et al.
Probabilistic Conformal Prediction with Approximate Conditional Validity
Vincent Plassier, Alexander Fishkov, Mohsen Guizani et al.
Pacmann: Efficient Private Approximate Nearest Neighbor Search
Mingxun Zhou, Elaine Shi, Giulia Fanti
Multiplicative Logit Adjustment Approximates Neural-Collapse-Aware Decision Boundary Adjustment
Naoya Hasegawa, Issei Sato
Neural Approximate Mirror Maps for Constrained Diffusion Models
Berthy Feng, Ricardo Baptista, Katherine Bouman
Approximate Inference in Collective Graphical Models
Daniel Sheldon, Tao Sun, Akshat Kumar et al.
Scaling Up Approximate Value Iteration with Options: Better Policies with Fewer Iterations
Timothy Mann, Shie Mannor
An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation Accuracy
Gavin Taylor, Connor Geer, David Piekut
Composite Quantization for Approximate Nearest Neighbor Search
Ting Zhang, Chao Du, Jingdong Wang
Communication-Efficient Distributed Optimization using an Approximate Newton-type Method
Ohad Shamir, Nati Srebro, Tong Zhang
Stochastic Backpropagation and Approximate Inference in Deep Generative Models
Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra
Approximate Policy Iteration Schemes: A Comparison
Bruno Scherrer
Sample-based approximate regularization
Philip Bachman, Amir-Massoud Farahmand, Doina Precup
The Benefits of Learning with Strongly Convex Approximate Inference
Ben London, Bert Huang, Lise Getoor
Tracking Approximate Solutions of Parameterized Optimization Problems over Multi-Dimensional (Hyper-)Parameter Domains
Katharina Blechschmidt, Joachim Giesen, Soeren Laue
Swept Approximate Message Passing for Sparse Estimation
Andre Manoel, Florent Krzakala, Eric Tramel et al.
Approximate Dynamic Programming for Two-Player Zero-Sum Markov Games
Julien Perolat, Bruno Scherrer, Bilal Piot et al.
Non-Stationary Approximate Modified Policy Iteration
Boris Lesner, Bruno Scherrer