Papers
1,821 papers found
Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks
Felix Dangel, Johannes Müller, Marius Zeinhofer
LibAMM: Empirical Insights into Approximate Computing for Accelerating Matrix Multiplication
Xianzhi Zeng, Wenchao Jiang, Shuhao Zhang
Training Data Attribution via Approximate Unrolling
Juhan Bae, Wu Lin, Jonathan Lorraine et al.
Optimal and Approximate Adaptive Stochastic Quantization
Ran Ben Basat, Yaniv Ben-Itzhak, Michael Mitzenmacher et al.
LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search
Elias Jääsaari, Ville Hyvönen, Teemu Roos
CSPG: Crossing Sparse Proximity Graphs for Approximate Nearest Neighbor Search
Ming Yang, Yuzheng Cai, Weiguo Zheng
Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradients
Yuri R. Fonseca, Caio F. L. Peixoto, Yuri F. Saporito
Computational Aspects of Bayesian Persuasion under Approximate Best Response
Kunhe Yang, Hanrui Zhang
Adaptable Pouring: Teaching Robots Not to Spill using Fast but Approximate Fluid Simulation
Tatiana Lopez-Guevara, Nicholas K Taylor, Michael U Gutmann et al.
Stochastic Optimal Control as Approximate Input Inference
Joe Watson, Hany Abdulsamad, Jan Peters
Learning Object Manipulation Skills via Approximate State Estimation from Real Videos
Vladimír Petrík, Makarand Tapaswi, Ivan Laptev et al.
Enabling Efficient, Reliable Real-World Reinforcement Learning with Approximate Physics-Based Models
Tyler Westenbroek, Jacob Levy, David Fridovich-Keil
BIRD: Engineering an Efficient CNF-XOR SAT Solver and Its Applications to Approximate Model Counting
Mate Soos, Kuldeep S. Meel
An Improved Quasi-Polynomial Algorithm for Approximate Well-Supported Nash Equilibria
Michail Fasoulakis, Evangelos Markakis
Approximate Inference of Outcomes in Probabilistic Elections
Batya Kenig, Benny Kimelfeld
Approximate Stream Reasoning with Metric Temporal Logic under Uncertainty
Daniel de Leng, Fredrik Heintz
EA-CG: An Approximate Second-Order Method for Training Fully-Connected Neural Networks
Sheng-Wei Chen, Chun-Nan Chou, Edward Y. Chang
Efficient Identification of Approximate Best Configuration of Training in Large Datasets
Silu Huang, Chi Wang, Bolin Ding et al.
Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs
Mayukh Das, Devendra Singh Dhami, Gautam Kunapuli et al.
Exact and Approximate Weighted Model Integration with Probability Density Functions Using Knowledge Compilation
Pedro Zuidberg Dos Martires, Anton Dries, Luc De Raedt
Interleave Variational Optimization with Monte Carlo Sampling: A Tale of Two Approximate Inference Paradigms
Qi Lou, Rina Dechter, Alexander Ihler
A Robust and Efficient Algorithm for the PnL Problem Using Algebraic Distance to Approximate the Reprojection Distance
Lipu Zhou, Yi Yang, Montiel Abello et al.
Neural Approximate Dynamic Programming for On-Demand Ride-Pooling
Sanket Shah, Meghna Lowalekar, Pradeep Varakantham
SPAN: A Stochastic Projected Approximate Newton Method
Xunpeng Huang, Xianfeng Liang, Zhengyang Liu et al.
Structure Learning for Approximate Solution of Many-Player Games
Zun Li, Michael Wellman