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02/03/2023
Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers
We propose a new class of linear Transformers called FourierLearner-Tran...
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02/02/2023
Efficient Graph Field Integrators Meet Point Clouds
We present two new classes of algorithms for efficient field integration...
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02/01/2023
FAVOR#: Sharp Attention Kernel Approximations via New Classes of Positive Random Features
The problem of efficient approximation of a linear operator induced by t...
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11/22/2022
Generalized Private Selection and Testing with High Confidence
Composition theorems are general and powerful tools that facilitate priv...
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11/11/2022
Õptimal Differentially Private Learning of Thresholds and Quasi-Concave Optimization
The problem of learning threshold functions is a fundamental one in mach...
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07/03/2022
Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs
CountSketch and Feature Hashing (the "hashing trick") are popular random...
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05/30/2022
Chefs' Random Tables: Non-Trigonometric Random Features
We introduce chefs' random tables (CRTs), a new class of non-trigonometr...
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02/28/2022
On the Robustness of CountSketch to Adaptive Inputs
CountSketch is a popular dimensionality reduction technique that maps ve...
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01/19/2021
ES-ENAS: Combining Evolution Strategies with Neural Architecture Search at No Extra Cost for Reinforcement Learning
We introduce ES-ENAS, a simple neural architecture search (NAS) algorith...
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10/25/2020
Differentially Private Weighted Sampling
Common datasets have the form of elements with keys (e.g., transactions ...
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09/30/2020
Rethinking Attention with Performers
We introduce Performers, Transformer architectures which can estimate re...
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06/05/2020
Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers
Transformer models have achieved state-of-the-art results across a diver...
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03/30/2020
Stochastic Flows and Geometric Optimization on the Orthogonal Group
We present a new class of stochastic, geometrically-driven optimization ...
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07/10/2019
Reinforcement Learning with Chromatic Networks
We present a new algorithm for finding compact neural networks encoding ...
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05/29/2019
Matrix-Free Preconditioning in Online Learning
We provide an online convex optimization algorithm with regret that inte...
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03/09/2019
Orthogonal Estimation of Wasserstein Distances
Wasserstein distances are increasingly used in a wide variety of applica...
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04/05/2017
Linear Additive Markov Processes
We introduce LAMP: the Linear Additive Markov Process. Transitions in LA...
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05/29/2016
