Sean Bell
Yiqun Liu
Sami Alsheikh
Yina Tang...
KDD
Oran Gafni
Lior Wolf
Yaniv Taigman
International Conference on Computer Vision (ICCV)
Gines Hidalgo
Yaadhav Raaj
Haroon Idrees
Donglai Xiang...
International Conference on Computer Vision (ICCV)
Noam Mor
Lior Wolf
Adam Polyak
Yaniv Taigman
International Conference on Learning Representations (ICLR)
Model-based Reinforcement Learning (MBRL) is a promising framework for learning control in a data-efficient manner…
Baohe Zhang, Raghu Rajan, Luis Pineda, Nathan Lambert, Andre Biedenkapp, Kurtland Chua, Frank Hutter, Roberto Calandra
The use of GPUs has proliferated for machine learning workflows and is now considered mainstream for many deep learning models…
Bilge Acun, Matthew Murphy, Xiaodong Wang, Jade Nie, Carole-Jean Wu, Kim Hazelwood
Standard results in stochastic convex optimization bound the number of samples that an algorithm needs to generate a point with small function value in expectation…
Damek Davis, Dmitriy Drusvyatskiy, Lin Xiao, Junyu Zhang
Inference in deep neural networks can be computationally expensive, and networks capable of anytime inference are important in scenarios where the amount of compute or quantity of input data varies over time.…
Adria Ruiz, Jakob Verbeek
We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.