Krzysztof Choromanski

Krzysztof Choromanski

Krzysztof Choromanski works on several aspects of machine learning and robotics. His current research interests include reinforcement learning and randomized methods such as nonlinear embeddings based on structured random feature maps and quasi-Monte-Carlo methods. He was also working on online nonparametric clustering for massive high-dimensional streams. Krzysztof is an author of several nonlinear embedding mechanisms based on structured matrices that can be used to speed up: neural network computations, kernel methods applying random feature maps, convex optimization solvers, quantization and soft clustering methods as well as several LSH-based algorithms. With his background in structural graph theory, he is also interested in applying graph theory and other combinatorial methods in machine learning.
Authored Publications
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    Robotic Table Tennis: A Case Study into a High Speed Learning System
    Jon Abelian
    Saminda Abeyruwan
    Michael Ahn
    Justin Boyd
    Erwin Johan Coumans
    Omar Escareno
    Wenbo Gao
    Navdeep Jaitly
    Juhana Kangaspunta
    Satoshi Kataoka
    Gus Kouretas
    Yuheng Kuang
    Corey Lynch
    Thinh Nguyen
    Ken Oslund
    Barney J. Reed
    Anish Shankar
    Avi Singh
    Grace Vesom
    Peng Xu
    Robotics: Science and Systems (2023)
    Hybrid Random Features
    Haoxian Chen
    Han Lin
    Yuanzhe Ma
    Arijit Sehanobish
    Michael Ryoo
    Jake Varley
    Andy Zeng
    Valerii Likhosherstov
    Dmitry Kalashnikov
    Adrian Weller
    International Conference on Learning Representations (ICLR) (2022)
    Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation
    Anthony G. Francis
    Dmitry Kalashnikov
    Edward Lee
    Jake Varley
    Leila Takayama
    Mikael Persson
    Peng Xu
    Stephen Tu
    Xuesu Xiao
    Conference on Robot Learning (2022) (to appear)
    Chefs’ Random Tables: Non-Trigonometric Random Features
    Valerii Likhosherstov
    Frederick Liu
    Adrian Weller
    NeurIPS 2022 (2022) (to appear)
    Sub-Linear Memory: How to Make Performers SLiM
    Valerii Likhosherstov
    Jared Davis
    Adrian Weller
    NeurIPS 2021
    Rethinking Attention with Performers
    Valerii Likhosherstov
    David Martin Dohan
    Peter Hawkins
    Jared Quincy Davis
    Afroz Mohiuddin
    Lukasz Kaiser
    Adrian Weller
    accepted to ICLR 2021 (oral presentation) (to appear)
    Debiasing a First-order Heuristic for Approximate Bi-level Optimization
    Valerii Likhosherstov
    Jared Davis
    Adrian Weller
    Thirty-eighth International Conference on Machine Learning (ICML 2021)