29 citations · 48 across the 4 of their papers we have counts for
8 papers
Chefs' Random Tables: Non-Trigonometric Random Features
Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey +3
We introduce chefs' random tables (CRTs), a new class of non-trigonometric random features (RFs) to approximate Gaussian and softmax kernels. CRTs are an alternative to standard ra…
Differentially Private Weighted Sampling
Edith Cohen, Ofir Geri, Tamas Sarlos +1
Common datasets have the form of elements with keys (e.g., transactions and products) and the goal is to perform analytics on the aggregated form of key and frequency pairs. A weig…
Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan +8
Transformer models have achieved state-of-the-art results across a diverse range of domains. However, concern over the cost of training the attention mechanism to learn complex dep…
Stochastic Flows and Geometric Optimization on the Orthogonal Group
Krzysztof Choromanski, David Cheikhi, Jared Davis +12
We present a new class of stochastic, geometrically-driven optimization algorithms on the orthogonal group and naturally reductive homogeneous manifolds obtained from the ac…
Reinforcement Learning with Chromatic Networks for Compact Architecture Search
Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder +6
We present a neural architecture search algorithm to construct compact reinforcement learning (RL) policies, by combining ENAS and ES in a highly scalable and intuitive way. By def…
Matrix-Free Preconditioning in Online Learning
Ashok Cutkosky, Tamas Sarlos
We provide an online convex optimization algorithm with regret that interpolates between the regret of an algorithm using an optimal preconditioning matrix and one using a diagonal…