The power of the dinur-nissim algorithm: breaking privacy of statistical and graph databases. - Krzysztof Choromanski; Tal Malkin (PODS, 2012)

Adaptive Anonymity via b-Matching. - Krzysztof Choromanski; Tony Jebara; Kui Tang (NIPS, 2013)

Tournaments and colouring. - Eli Berger; Krzysztof Choromanski; Maria Chudnovsky; Jacob Fox; Martin Loebl; Alex Scott 001; Paul D. Seymour; Stéphan Thomassé (J. Comb. Theory B, 2013)

Upper Bounds for Erdös-Hajnal Coefficients of Tournaments. - Krzysztof Choromanski (J. Graph Theory, 2013)

Notes on using Determinantal Point Processes for Clustering with Applications to Text Clustering. - Apoorv Agarwal; Anna Choromanska; Krzysztof Choromanski (CoRR, 2014)

Differentially- and non-differentially-private random decision trees. - Mariusz Bojarski; Anna Choromanska; Krzysztof Choromanski; Yann LeCun (CoRR, 2014)

Tournaments with near-linear transitive subsets. - Krzysztof Choromanski; Maria Chudnovsky; Paul D. Seymour (J. Comb. Theory B, 2014)

An Optimal Online Algorithm For Retrieving Heavily Perturbed Statistical Databases In The Low-Dimensional Querying Model. - Krzysztof Marcin Choromanski; Afshin Rostamizadeh; Umar Syed (CIKM, 2015)

Learning how to rank from heavily perturbed statistics - digraph clustering approach. - Krzysztof Choromanski (CoRR, 2015)

Efficient data hashing with structured binary embeddings. - Krzysztof Choromanski (CoRR, 2015)

Coloring tournaments with forbidden substructures. - Krzysztof Choromanski; Tony Jebara (CoRR, 2015)

Fast Online Clustering with Randomized Skeleton Sets. - Krzysztof Choromanski; Sanjiv Kumar; Xiaofeng Liu (CoRR, 2015)

An $ tilde{O}( frac{1}{ sqrt{T}})$-error online algorithm for retrieving heavily perturbated statistical databases in the low-dimensional querying mode. - Krzysztof Choromanski; Afshin Rostamizadeh; Umar Syed (CoRR, 2015)

Forcing large transitive subtournaments. - Eli Berger; Krzysztof Choromanski; Maria Chudnovsky (J. Comb. Theory B, 2015)

EH-suprema of tournaments with no nontrivial homogeneous sets. - Krzysztof Choromanski (J. Comb. Theory B, 2015)

Quantization based Fast Inner Product Search. - Ruiqi Guo; Sanjiv Kumar; Krzysztof Choromanski; David Simcha (AISTATS, 2016)

Binary embeddings with structured hashed projections. - Anna Choromanska; Krzysztof Choromanski; Mariusz Bojarski; Tony Jebara; Sanjiv Kumar; Yann LeCun (ICML, 2016)

Recycling Randomness with Structure for Sublinear time Kernel Expansions. - Krzysztof Choromanski; Vikas Sindhwani (ICML, 2016)

Orthogonal Random Features. - Felix X. Yu; Ananda Theertha Suresh; Krzysztof Marcin Choromanski; Daniel N. Holtmann-Rice; Sanjiv Kumar (NIPS, 2016)

VisualBackProp: visualizing CNNs for autonomous driving. - Mariusz Bojarski; Anna Choromanska; Krzysztof Choromanski; Bernhard Firner; Larry D. Jackel; Urs Muller; Karol Zieba (CoRR, 2016)

On the boosting ability of top-down decision tree learning algorithm for multiclass classification. - Anna Choromanska; Krzysztof Choromanski; Mariusz Bojarski (CoRR, 2016)

Fast nonlinear embeddings via structured matrices. - Krzysztof Choromanski; Francois Fagan (CoRR, 2016)

TripleSpin - a generic compact paradigm for fast machine learning computations. - Krzysztof Choromanski; Francois Fagan; Cédric Gouy-Pailler; Anne Morvan; Tamás Sarlós; Jamal Atif (CoRR, 2016)

Differentially-private learning of low dimensional manifolds. - Anna Choromanska; Krzysztof Choromanski; Geetha Jagannathan; Claire Monteleoni (Theor. Comput. Sci., 2016)

Structured adaptive and random spinners for fast machine learning computations. - Mariusz Bojarski; Anna Choromanska; Krzysztof Choromanski; Francois Fagan; Cédric Gouy-Pailler; Anne Morvan; Nourhan Sakr; Tamás Sarlós; Jamal Atif (AISTATS, 2017)

The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings. - Krzysztof Marcin Choromanski; Mark Rowland 001; Adrian Weller (NIPS, 2017)

On Blackbox Backpropagation and Jacobian Sensing. - Krzysztof Marcin Choromanski; Vikas Sindhwani (NIPS, 2017)

Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a Car. - Mariusz Bojarski; Philip Yeres; Anna Choromanska; Krzysztof Choromanski; Bernhard Firner; Lawrence D. Jackel; Urs Muller (CoRR, 2017)

Graph sketching-based Massive Data Clustering. - Anne Morvan; Krzysztof Choromanski; Cédric Gouy-Pailler; Jamal Atif (CoRR, 2017)

Manifold Regularization for Kernelized LSTD. - Xinyan Yan; Krzysztof Choromanski; Byron Boots; Vikas Sindhwani (CoRR, 2017)

The Geometry of Random Features. - Krzysztof Choromanski; Mark Rowland 001; Tamás Sarlós; Vikas Sindhwani; Richard E. Turner; Adrian Weller (AISTATS, 2018)

Initialization matters: Orthogonal Predictive State Recurrent Neural Networks. - Krzysztof Choromanski; Carlton Downey; Byron Boots (ICLR (Poster), 2018)

Structured Evolution with Compact Architectures for Scalable Policy Optimization. - Krzysztof Choromanski; Mark Rowland 001; Vikas Sindhwani; Richard E. Turner; Adrian Weller (ICML, 2018)

VisualBackProp: Efficient Visualization of CNNs for Autonomous Driving. - Mariusz Bojarski; Anna Choromanska; Krzysztof Choromanski; Bernhard Firner; Larry J. Ackel; Urs Muller; Philip Yeres; Karol Zieba (ICRA, 2018)

Optimizing Simulations with Noise-Tolerant Structured Exploration. - Krzysztof Choromanski; Atil Iscen; Vikas Sindhwani; Jie Tan 001; Erwin Coumans (ICRA, 2018)

Geometrically Coupled Monte Carlo Sampling. - Mark Rowland 001; Krzysztof Choromanski; François Chalus; Aldo Pacchiano; Tamás Sarlós; Richard E. Turner; Adrian Weller (NeurIPS, 2018)

Adaptive anonymization of data using b-edge cover. - Arif Khan 005; Krzysztof Choromanski; Alex Pothen; S. M. Ferdous; Mahantesh Halappanavar; Antonino Tumeo (SC, 2018)

Graph sketching-based Space-efficient Data Clustering. - Anne Morvan; Krzysztof Choromanski; Cédric Gouy-Pailler; Jamal Atif (SDM, 2018)

Learning-based Air Data System for Safe and Efficient Control of Fixed-wing Aerial Vehicles. - Krzysztof Choromanski; Vikas Sindhwani; Brandon Jones; Damien Jourdan; Maciej Chociej; Byron Boots (SSRR, 2018)

Excluding Hooks and their Complements. - Krzysztof Choromanski; Dvir Falik; Anita Liebenau; Viresh Patel; Marcin Pilipczuk (Electron. J. Comb., 2018)

On the Needs for Rotations in Hypercubic Quantization Hashing. - Anne Morvan; Antoine Souloumiac; Krzysztof Choromanski; Cédric Gouy-Pailler; Jamal Atif (CoRR, 2018)

Excluding pairs of tournaments. - Krzysztof Choromanski (J. Graph Theory, 2018)

KAMA-NNs: Low-dimensional Rotation Based Neural Networks. - Krzysztof Choromanski; Aldo Pacchiano; Jeffrey Pennington; Yunhao Tang (AISTATS, 2019)

Orthogonal Estimation of Wasserstein Distances. - Mark Rowland 001; Jiri Hron; Yunhao Tang; Krzysztof Choromanski; Tamás Sarlós; Adrian Weller (AISTATS, 2019)

Provably Robust Blackbox Optimization for Reinforcement Learning. - Krzysztof Choromanski; Aldo Pacchiano; Jack Parker-Holder; Yunhao Tang; Deepali Jain; Yuxiang Yang 007; Atil Iscen; Jasmine Hsu; Vikas Sindhwani (CoRL, 2019)

Unifying Orthogonal Monte Carlo Methods. - Krzysztof Choromanski; Mark Rowland 001; Wenyu Chen 003; Adrian Weller (ICML, 2019)

From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization. - Krzysztof Choromanski; Aldo Pacchiano; Jack Parker-Holder; Yunhao Tang; Vikas Sindhwani (NeurIPS, 2019)

When random search is not enough: Sample-Efficient and Noise-Robust Blackbox Optimization of RL Policies. - Krzysztof Choromanski; Aldo Pacchiano; Jack Parker-Holder; Jasmine Hsu; Atil Iscen; Deepali Jain; Vikas Sindhwani (CoRR, 2019)

Adaptive Sample-Efficient Blackbox Optimization via ES-active Subspaces. - Krzysztof Choromanski; Aldo Pacchiano; Jack Parker-Holder; Yunhao Tang (CoRR, 2019)

Structured Monte Carlo Sampling for Nonisotropic Distributions via Determinantal Point Processes. - Krzysztof Choromanski; Aldo Pacchiano; Jack Parker-Holder; Yunhao Tang (CoRR, 2019)

Wasserstein Reinforcement Learning. - Aldo Pacchiano; Jack Parker-Holder; Yunhao Tang; Anna Choromanska; Krzysztof Choromanski; Michael I. Jordan (CoRR, 2019)

Reinforcement Learning with Chromatic Networks. - Xingyou Song; Krzysztof Choromanski; Jack Parker-Holder; Yunhao Tang; Wenbo Gao; Aldo Pacchiano; Tamás Sarlós; Deepali Jain; Yuxiang Yang 007 (CoRR, 2019)

On the Erdős-Hajnal conjecture for six-vertex tournaments. - Eli Berger; Krzysztof Choromanski; Maria Chudnovsky (Eur. J. Comb., 2019)

Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes. - Krzysztof Choromanski; Aldo Pacchiano; Jack Parker-Holder; Yunhao Tang (AISTATS, 2020)

Variance Reduction for Evolution Strategies via Structured Control Variates. - Yunhao Tang; Krzysztof Choromanski; Alp Kucukelbir (AISTATS, 2020)

ES-MAML: Simple Hessian-Free Meta Learning. - Xingyou Song; Wenbo Gao; Yuxiang Yang 007; Krzysztof Choromanski; Aldo Pacchiano; Yunhao Tang (ICLR, 2020)

Ready Policy One: World Building Through Active Learning. - Philip J. Ball; Jack Parker-Holder; Aldo Pacchiano; Krzysztof Choromanski; Stephen J. Roberts (ICML, 2020)

Stochastic Flows and Geometric Optimization on the Orthogonal Group. - Krzysztof Choromanski; David Cheikhi; Jared Davis; Valerii Likhosherstov; Achille Nazaret; Achraf Bahamou; Xingyou Song; Mrugank Akarte; Jack Parker-Holder; Jacob Bergquist; Yuan Gao 038; Aldo Pacchiano; et al. (ICML, 2020)

Learning to Score Behaviors for Guided Policy Optimization. - Aldo Pacchiano; Jack Parker-Holder; Yunhao Tang; Krzysztof Choromanski; Anna Choromanska; Michael I. Jordan (ICML, 2020)

Unsupervised Anomaly Detection for Self-flying Delivery Drones. - Vikas Sindhwani; Hakim Sidahmed; Krzysztof Choromanski; Brandon Jones (ICRA, 2020)

Robotic Table Tennis with Model-Free Reinforcement Learning. - Wenbo Gao; Laura Graesser; Krzysztof Choromanski; Xingyou Song; Nevena Lazic; Pannag Sanketi; Vikas Sindhwani; Navdeep Jaitly (IROS, 2020)

Rapidly Adaptable Legged Robots via Evolutionary Meta-Learning. - Xingyou Song; Yuxiang Yang 007; Krzysztof Choromanski; Ken Caluwaerts; Wenbo Gao; Chelsea Finn; Jie Tan 001 (IROS, 2020)

Ode to an ODE. - Krzysztof Marcin Choromanski; Jared Quincy Davis; Valerii Likhosherstov; Xingyou Song; Jean-Jacques E. Slotine; Jacob Varley; Honglak Lee; Adrian Weller; Vikas Sindhwani (NeurIPS, 2020)

Demystifying Orthogonal Monte Carlo and Beyond. - Han Lin; Haoxian Chen 002; Krzysztof Marcin Choromanski; Tianyi Zhang; Clement Laroche (NeurIPS, 2020)

Effective Diversity in Population Based Reinforcement Learning. - Jack Parker-Holder; Aldo Pacchiano; Krzysztof Marcin Choromanski; Stephen J. Roberts (NeurIPS, 2020)

CWY Parametrization for Scalable Learning of Orthogonal and Stiefel Matrices. - Valerii Likhosherstov; Jared Davis; Krzysztof Choromanski; Adrian Weller (CoRR, 2020)

Time Dependence in Non-Autonomous Neural ODEs. - Jared Quincy Davis; Krzysztof Choromanski; Jake Varley; Honglak Lee; Jean-Jacques E. Slotine; Valerii Likhosterov; Adrian Weller; Ameesh Makadia; Vikas Sindhwani (CoRR, 2020)

Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers. - Krzysztof Choromanski; Valerii Likhosherstov; David Dohan; Xingyou Song; Jared Davis; Tamás Sarlós; David Belanger 002; Lucy J. Colwell; Adrian Weller (CoRR, 2020)

UFO-BLO: Unbiased First-Order Bilevel Optimization. - Valerii Likhosherstov; Xingyou Song; Krzysztof Choromanski; Jared Davis; Adrian Weller (CoRR, 2020)

Online Hyper-parameter Tuning in Off-policy Learning via Evolutionary Strategies. - Yunhao Tang; Krzysztof Choromanski (CoRR, 2020)

An Ode to an ODE. - Krzysztof Choromanski; Jared Quincy Davis; Valerii Likhosherstov; Xingyou Song; Jean-Jacques E. Slotine; Jacob Varley; Honglak Lee; Adrian Weller; Vikas Sindhwani (CoRR, 2020)

On Optimism in Model-Based Reinforcement Learning. - Aldo Pacchiano; Philip J. Ball; Jack Parker-Holder; Krzysztof Choromanski; Stephen Roberts 001 (CoRR, 2020)

CWY Parametrization: a Solution for Parallelized Optimization of Orthogonal and Stiefel Matrices. - Valerii Likhosherstov; Jared Davis; Krzysztof Choromanski; Adrian Weller (AISTATS, 2021)

Rethinking Attention with Performers. - Krzysztof Marcin Choromanski; Valerii Likhosherstov; David Dohan; Xingyou Song; Andreea Gane; Tamás Sarlós; Peter Hawkins; Jared Quincy Davis; Afroz Mohiuddin; Lukasz Kaiser; David Benjamin Belanger; Lucy J. Colwell; et al. (ICLR, 2021)

Catformer: Designing Stable Transformers via Sensitivity Analysis. - Jared Quincy Davis; Albert Gu; Krzysztof Choromanski; Tri Dao; Christopher Ré; Chelsea Finn; Percy Liang (ICML, 2021)

Debiasing a First-order Heuristic for Approximate Bi-level Optimization. - Valerii Likhosherstov; Xingyou Song; Krzysztof Choromanski; Jared Quincy Davis; Adrian Weller (ICML, 2021)

Sub-Linear Memory: How to Make Performers SLiM. - Valerii Likhosherstov; Krzysztof Marcin Choromanski; Jared Quincy Davis; Xingyou Song; Adrian Weller (NeurIPS, 2021)

Towards tractable optimism in model-based reinforcement learning. - Aldo Pacchiano; Philip J. Ball; Jack Parker-Holder; Krzysztof Choromanski; Stephen Roberts 001 (UAI, 2021)

MLGO: a Machine Learning Guided Compiler Optimizations Framework. - Mircea Trofin; Yundi Qian; Eugene Brevdo; Zinan Lin 001; Krzysztof Choromanski; David Li (CoRR, 2021)

ES-ENAS: Combining Evolution Strategies with Neural Architecture Search at No Extra Cost for Reinforcement Learning. - Xingyou Song; Krzysztof Choromanski; Jack Parker-Holder; Yunhao Tang; Daiyi Peng; Deepali Jain; Wenbo Gao; Aldo Pacchiano; Tamás Sarlós; Yuxiang Yang 007 (CoRR, 2021)

Unlocking Pixels for Reinforcement Learning via Implicit Attention. - Krzysztof Choromanski; Deepali Jain; Jack Parker-Holder; Xingyou Song; Valerii Likhosherstov; Anirban Santara; Aldo Pacchiano; Yunhao Tang; Adrian Weller (CoRR, 2021)

On the Expressive Power of Self-Attention Matrices. - Valerii Likhosherstov; Krzysztof Choromanski; Adrian Weller (CoRR, 2021)

Graph Kernel Attention Transformers. - Krzysztof Choromanski; Han Lin; Haoxian Chen 002; Jack Parker-Holder (CoRR, 2021)

PolyViT: Co-training Vision Transformers on Images, Videos and Audio. - Valerii Likhosherstov; Anurag Arnab; Krzysztof Choromanski; Mario Lucic; Yi Tay; Adrian Weller; Mostafa Dehghani 001 (CoRR, 2021)

i-Sim2Real: Reinforcement Learning of Robotic Policies in Tight Human-Robot Interaction Loops. - Saminda Wishwajith Abeyruwan; Laura Graesser; David B. D'Ambrosio; Avi Singh; Anish Shankar; Alex Bewley; Deepali Jain; Krzysztof Marcin Choromanski; Pannag R. Sanketi (CoRL, 2022)

Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation. - Xuesu Xiao; Tingnan Zhang; Krzysztof Marcin Choromanski; Tsang-Wei Edward Lee; Anthony G. Francis; Jake Varley; Stephen Tu; Sumeet Singh; Peng Xu 010; Fei Xia 002; Sven Mikael Persson; Dmitry Kalashnikov; et al. (CoRL, 2022)

Improving The Latency And Quality Of Cascaded Encoders. - Tara N. Sainath; Yanzhang He; Arun Narayanan; Rami Botros; Weiran Wang; David Qiu; Chung-Cheng Chiu; Rohit Prabhavalkar; Alexander Gruenstein; Anmol Gulati; Bo Li 028; David Rybach; et al. (ICASSP, 2022)

Hybrid Random Features. - Krzysztof Marcin Choromanski; Han Lin; Haoxian Chen 002; Arijit Sehanobish; Yuanzhe Ma; Deepali Jain; Jake Varley; Andy Zeng 001; Michael S. Ryoo; Valerii Likhosherstov; Dmitry Kalashnikov; Vikas Sindhwani; et al. (ICLR, 2022)

From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers. - Krzysztof Choromanski; Han Lin; Haoxian Chen 002; Tianyi Zhang; Arijit Sehanobish; Valerii Likhosherstov; Jack Parker-Holder; Tamás Sarlós; Adrian Weller; Thomas Weingarten (ICML, 2022)

Chefs' Random Tables: Non-Trigonometric Random Features. - Valerii Likhosherstov; Krzysztof Marcin Choromanski; Kumar Avinava Dubey; Frederick Liu; Tamás Sarlós; Adrian Weller (NeurIPS, 2022)

Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language. - Andy Zeng 001; Adrian Wong; Stefan Welker; Krzysztof Choromanski; Federico Tombari; Aveek Purohit; Michael S. Ryoo; Vikas Sindhwani; Johnny Lee; Vincent Vanhoucke; Pete Florence (CoRR, 2022)

Implicit Two-Tower Policies. - Yunfan Zhao; Qingkai Pan; Krzysztof Choromanski; Deepali Jain; Vikas Sindhwani (CoRR, 2022)

Multiple View Performers for Shape Completion. - David Watkins-Valls; Peter E. Allen; Krzysztof Choromanski; Jacob Varley; Nicholas R. Waytowich (CoRR, 2022)

Automated Deep Aberration Detection from Chromosome Karyotype Images. - Zahra Shamsi; Drew Bryant; Jacob Wilson; Xiaoyu Qu; Avinava Dubey; Konik Kothari; Mostafa Dehghani 001; Mariya Chavarha; Valerii Likhosherstov; Brian Williams; Michael Frumkin; Fred Appelbaum; et al. (CoRR, 2022)

Tournaments and the strong Erdős-Hajnal Property. - Eli Berger; Krzysztof Choromanski; Maria Chudnovsky; Shira Zerbib (Eur. J. Comb., 2022)

A Theoretical and Empirical Comparison of Gradient Approximations in Derivative-Free Optimization. - Albert S. Berahas; Liyuan Cao; Krzysztof Choromanski; Katya Scheinberg (Found. Comput. Math., 2022)

On the Expressive Flexibility of Self-Attention Matrices. - Valerii Likhosherstov; Krzysztof Choromanski; Adrian Weller (AAAI, 2023)

RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control. - Brianna Zitkovich; Tianhe Yu; Sichun Xu; Peng Xu 010; Ted Xiao; Fei Xia 002; Jialin Wu; Paul Wohlhart; Stefan Welker; Ayzaan Wahid; Quan Vuong; Vincent Vanhoucke; et al. (CoRL, 2023)

Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language. - Andy Zeng 001; Maria Attarian; Brian Ichter; Krzysztof Marcin Choromanski; Adrian Wong; Stefan Welker; Federico Tombari; Aveek Purohit; Michael S. Ryoo; Vikas Sindhwani; Johnny Lee; Vincent Vanhoucke; et al. (ICLR, 2023)

Taming graph kernels with random features. - Krzysztof Marcin Choromanski (ICML, 2023)

Efficient Graph Field Integrators Meet Point Clouds. - Krzysztof Marcin Choromanski; Arijit Sehanobish; Han Lin; Yunfan Zhao; Eli Berger; Tetiana Parshakova; Alvin Pan; David Watkins; Tianyi Zhang; Valerii Likhosherstov; Somnath Basu Roy Chowdhury; Kumar Avinava Dubey; et al. (ICML, 2023)

Simplex Random Features. - Isaac Reid; Krzysztof Marcin Choromanski; Valerii Likhosherstov; Adrian Weller (ICML, 2023)

Agile Catching with Whole-Body MPC and Blackbox Policy Learning. - Saminda Abeyruwan; Alex Bewley; Nicholas Matthew Boffi; Krzysztof Marcin Choromanski; David B. D'Ambrosio; Deepali Jain; Pannag R. Sanketi; Anish Shankar; Vikas Sindhwani; Sumeet Singh; Jean-Jacques E. Slotine; Stephen Tu (L4DC, 2023)

Mnemosyne: Learning to Train Transformers with Transformers. - Deepali Jain; Krzysztof Marcin Choromanski; Kumar Avinava Dubey; Sumeet Singh; Vikas Sindhwani; Tingnan Zhang; Jie Tan 001 (NeurIPS, 2023)

Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel. - Valerii Likhosherstov; Krzysztof Marcin Choromanski; Kumar Avinava Dubey; Frederick Liu; Tamás Sarlós; Adrian Weller (NeurIPS, 2023)

Quasi-Monte Carlo Graph Random Features. - Isaac Reid; Adrian Weller; Krzysztof Marcin Choromanski (NeurIPS, 2023)

Robotic Table Tennis: A Case Study into a High Speed Learning System. - David B. D'Ambrosio; Navdeep Jaitly; Vikas Sindhwani; Ken Oslund; Peng Xu 010; Nevena Lazic; Anish Shankar; Tianli Ding; Jonathan Abelian; Erwin Coumans; Gus Kouretas; Thinh Nguyen; et al. (Robotics: Science and Systems, 2023)

FAVOR#: Sharp Attention Kernel Approximations via New Classes of Positive Random Features. - Valerii Likhosherstov; Krzysztof Choromanski; Avinava Dubey; Frederick Liu; Tamás Sarlós; Adrian Weller (CoRR, 2023)

Practical Conformer: Optimizing size, speed and flops of Conformer for on-Device and cloud ASR. - Rami Botros; Anmol Gulati; Tara N. Sainath; Krzysztof Choromanski; Ruoming Pang; Trevor Strohman; Weiran Wang; Jiahui Yu (CoRR, 2023)

Robotic Table Tennis: A Case Study into a High Speed Learning System. - David B. D'Ambrosio; Jonathan Abelian; Saminda Abeyruwan; Michael Ahn; Alex Bewley; Justin Boyd; Krzysztof Choromanski; Omar Cortes; Erwin Coumans; Tianli Ding; Wenbo Gao; Laura Graesser; et al. (CoRR, 2023)

Augmenting conformers with structured state space models for online speech recognition. - Haozhe Shan; Albert Gu; Zhong Meng; Weiran Wang; Krzysztof Choromanski; Tara N. Sainath (CoRR, 2023)

Universal Graph Random Features. - Isaac Reid; Krzysztof Choromanski; Eli Berger; Adrian Weller (CoRR, 2023)

PolyViT: Co-training Vision Transformers on Images, Videos and Audio. - Valerii Likhosherstov; Anurag Arnab; Krzysztof Marcin Choromanski; Mario Lucic; Yi Tay; Mostafa Dehghani 001 (Trans. Mach. Learn. Res., 2023)

Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. - Krzysztof Choromanski; Shanda Li; Valerii Likhosherstov; Kumar Avinava Dubey; Shengjie Luo; Di He 001; Yiming Yang; Tamás Sarlós; Thomas Weingarten; Adrian Weller (AISTATS, 2024)

Modeling the Real World with High-Density Visual Particle Dynamics. - William F. Whitney; Jake Varley; Deepali Jain; Krzysztof Marcin Choromanski; Sumeet Singh; Vikas Sindhwani (CoRL, 2024)

Augmenting Conformers With Structured State-Space Sequence Models For Online Speech Recognition. - Haozhe Shan; Albert Gu; Zhong Meng; Weiran Wang; Krzysztof Choromanski; Tara N. Sainath (ICASSP, 2024)

Repelling Random Walks. - Isaac Reid; Eli Berger; Krzysztof Marcin Choromanski; Adrian Weller (ICLR, 2024)

General Graph Random Features. - Isaac Reid; Krzysztof Marcin Choromanski; Eli Berger; Adrian Weller (ICLR, 2024)

Scalable Neural Network Kernels. - Arijit Sehanobish; Krzysztof Marcin Choromanski; Yunfan Zhao; Kumar Avinava Dubey; Valerii Likhosherstov (ICLR, 2024)

SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention. - Isabel Leal; Krzysztof Choromanski; Deepali Jain; Avinava Dubey; Jake Varley; Michael S. Ryoo; Yao Lu 006; Frederick Liu; Vikas Sindhwani; Quan Vuong; Tamás Sarlós; Ken Oslund; et al. (ICRA, 2024)

Embodied AI with Two Arms: Zero-shot Learning, Safety and Modularity. - Jake Varley; Sumeet Singh; Deepali Jain; Krzysztof Choromanski; Andy Zeng 001; Somnath Basu Roy Chowdhury; Avinava Dubey; Vikas Sindhwani (IROS, 2024)

Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers. - Krzysztof Marcin Choromanski; Arijit Sehanobish; Somnath Basu Roy Chowdhury; Han Lin; Kumar Avinava Dubey; Tamás Sarlós; Snigdha Chaturvedi (NeurIPS, 2024)

Structured Unrestricted-Rank Matrices for Parameter Efficient Finetuning. - Arijit Sehanobish; Kumar Avinava Dubey; Krzysztof Marcin Choromanski; Somnath Basu Roy Chowdhury; Deepali Jain; Vikas Sindhwani; Snigdha Chaturvedi (NeurIPS, 2024)

Variance-Reducing Couplings for Random Features: Perspectives from Optimal Transport. - Isaac Reid; Stratis Markou; Krzysztof Choromanski; Richard E. Turner; Adrian Weller (CoRR, 2024)

Structured Unrestricted-Rank Matrices for Parameter Efficient Fine-tuning. - Arijit Sehanobish; Avinava Dubey; Krzysztof Choromanski; Somnath Basu Roy Chowdhury; Deepali Jain; Vikas Sindhwani; Snigdha Chaturvedi (CoRR, 2024)

Modeling the Real World with High-Density Visual Particle Dynamics. - William F. Whitney; Jacob Varley; Deepali Jain; Krzysztof Choromanski; Sumeet Singh; Vikas Sindhwani (CoRR, 2024)

Achieving Human Level Competitive Robot Table Tennis. - David B. D'Ambrosio; Saminda Abeyruwan; Laura Graesser; Atil Iscen; Heni Ben Amor; Alex Bewley; Barney J. Reed; Krista Reymann; Leila Takayama; Yuval Tassa; Krzysztof Choromanski; Erwin Coumans; et al. (CoRR, 2024)

Magnituder Layers for Implicit Neural Representations in 3D. - Sang Min Kim; Byeongchan Kim; Arijit Sehanobish; Krzysztof Choromanski; Dongseok Shim; Avinava Dubey; Min-hwan Oh (CoRR, 2024)

Optimal Time Complexity Algorithms for Computing General Random Walk Graph Kernels on Sparse Graphs. - Krzysztof Marcin Choromanski; Isaac Reid; Arijit Sehanobish; Kumar Avinava Dubey (AISTATS, 2025)

Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning. - Somnath Basu Roy Chowdhury; Krzysztof Marcin Choromanski; Arijit Sehanobish; Kumar Avinava Dubey; Snigdha Chaturvedi (ICLR, 2025)

Linear Transformer Topological Masking with Graph Random Features. - Isaac Reid; Kumar Avinava Dubey; Deepali Jain; William F. Whitney; Amr Ahmed 001; Joshua Ainslie; Alex Bewley; Mithun George Jacob; Aranyak Mehta; David Rendleman; Connor Schenck; Richard E. Turner; et al. (ICLR, 2025)

Variance-Reducing Couplings for Random Features. - Isaac Reid; Stratis Markou; Krzysztof Marcin Choromanski; Richard E. Turner; Adrian Weller (ICLR, 2025)

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING. - Connor Schenck; Isaac Reid; Mithun George Jacob; Alex Bewley; Joshua Ainslie; David Rendleman; Deepali Jain; Mohit Sharma 001; Avinava Dubey; Ayzaan Wahid; Sumeet Singh; René Wagner; et al. (CoRR, 2025)

Gemini Robotics: Bringing AI into the Physical World. - Gemini Robotics Team; Saminda Abeyruwan; Joshua Ainslie; Jean-Baptiste Alayrac; Montserrat Gonzalez Arenas; Travis Armstrong; Ashwin Balakrishna; Robert Baruch; Maria Bauzá 001; Michiel Blokzijl; Steven Bohez; Konstantinos Bousmalis; et al. (CoRR, 2025)