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09/15/2023
Augmenting conformers with structured state space models for online speech recognition
Online speech recognition, where the model only accesses context to the ...
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09/06/2023
Robotic Table Tennis: A Case Study into a High Speed Learning System
We present a deep-dive into a real-world robotic learning system that, i...
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07/28/2023
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
We study how vision-language models trained on Internet-scale data can b...
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06/14/2023
Agile Catching with Whole-Body MPC and Blackbox Policy Learning
We address a benchmark task in agile robotics: catching objects thrown a...
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05/21/2023
Quasi-Monte Carlo Graph Random Features
We present a novel mechanism to improve the accuracy of the recently-int...
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04/29/2023
Taming graph kernels with random features
We introduce in this paper the mechanism of graph random features (GRFs)...
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03/31/2023
Practical Conformer: Optimizing size, speed and flops of Conformer for on-Device and cloud ASR
Conformer models maintain a large number of internal states, the vast ma...
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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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01/31/2023
Simplex Random Features
We present Simplex Random Features (SimRFs), a new random feature (RF) m...
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09/22/2022
Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation
Despite decades of research, existing navigation systems still face real...
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09/13/2022
Multiple View Performers for Shape Completion
We propose the Multiple View Performer (MVP) - a new architecture for 3D...
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08/02/2022
Implicit Two-Tower Policies
We present a new class of structured reinforcement learning policy-archi...
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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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04/01/2022
Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language
Large foundation models can exhibit unique capabilities depending on the...
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11/25/2021
PolyViT: Co-training Vision Transformers on Images, Videos and Audio
Can we train a single transformer model capable of processing multiple m...
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10/08/2021
Hybrid Random Features
We propose a new class of random feature methods for linearizing softmax...
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07/16/2021
Graph Kernel Attention Transformers
We introduce a new class of graph neural networks (GNNs), by combining s...
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06/07/2021
On the Expressive Power of Self-Attention Matrices
Transformer networks are able to capture patterns in data coming from ma...
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06/04/2021
Debiasing a First-order Heuristic for Approximate Bi-level Optimization
Approximate bi-level optimization (ABLO) consists of (outer-level) optim...
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02/08/2021
Unlocking Pixels for Reinforcement Learning via Implicit Attention
There has recently been significant interest in training reinforcement l...
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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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01/13/2021
MLGO: a Machine Learning Guided Compiler Optimizations Framework
Leveraging machine-learning (ML) techniques for compiler optimizations h...
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12/21/2020
Sub-Linear Memory: How to Make Performers SLiM
The Transformer architecture has revolutionized deep learning on sequent...
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09/30/2020
Rethinking Attention with Performers
We introduce Performers, Transformer architectures which can estimate re...
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06/21/2020
On Optimism in Model-Based Reinforcement Learning
The principle of optimism in the face of uncertainty is prevalent throug...
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06/19/2020
An Ode to an ODE
We present a new paradigm for Neural ODE algorithms, calledODEtoODE, whe...
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06/13/2020
Online Hyper-parameter Tuning in Off-policy Learning via Evolutionary Strategies
Off-policy learning algorithms have been known to be sensitive to the ch...
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06/05/2020
UFO-BLO: Unbiased First-Order Bilevel Optimization
Bilevel optimization (BLO) is a popular approach with many applications ...
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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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05/27/2020
Demystifying Orthogonal Monte Carlo and Beyond
Orthogonal Monte Carlo (OMC) is a very effective sampling algorithm impo...
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05/05/2020
Time Dependence in Non-Autonomous Neural ODEs
Neural Ordinary Differential Equations (ODEs) are elegant reinterpretati...
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04/18/2020
CWY Parametrization for Scalable Learning of Orthogonal and Stiefel Matrices
In this paper we propose a new approach for optimization over orthogonal...
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03/31/2020
Robotic Table Tennis with Model-Free Reinforcement Learning
We propose a model-free algorithm for learning efficient policies capabl...
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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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03/02/2020
Rapidly Adaptable Legged Robots via Evolutionary Meta-Learning
Learning adaptable policies is crucial for robots to operate autonomousl...
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02/07/2020
Ready Policy One: World Building Through Active Learning
Model-Based Reinforcement Learning (MBRL) offers a promising direction f...
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02/03/2020
Effective Diversity in Population-Based Reinforcement Learning
Maintaining a population of solutions has been shown to increase explora...
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09/25/2019
ES-MAML: Simple Hessian-Free Meta Learning
We introduce ES-MAML, a new framework for solving the model agnostic met...
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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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06/11/2019
Wasserstein Reinforcement Learning
We propose behavior-driven optimization via Wasserstein distances (WDs) ...
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05/29/2019
Variance Reduction for Evolution Strategies via Structured Control Variates
Evolution Strategies (ES) are a powerful class of blackbox optimization ...
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05/29/2019
Structured Monte Carlo Sampling for Nonisotropic Distributions via Determinantal Point Processes
We propose a new class of structured methods for Monte Carlo (MC) sampli...
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05/29/2019
Linear interpolation gives better gradients than Gaussian smoothing in derivative-free optimization
In this paper, we consider derivative free optimization problems, where ...
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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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03/07/2019
Adaptive Sample-Efficient Blackbox Optimization via ES-active Subspaces
We present a new algorithm ASEBO for conducting optimization of high-dim...
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03/07/2019
When random search is not enough: Sample-Efficient and Noise-Robust Blackbox Optimization of RL Policies
Interest in derivative-free optimization (DFO) and "evolutionary strateg...
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05/20/2018
Optimizing Simulations with Noise-Tolerant Structured Exploration
We propose a simple drop-in noise-tolerant replacement for the standard ...
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04/06/2018
Structured Evolution with Compact Architectures for Scalable Policy Optimization
We present a new method of blackbox optimization via gradient approximat...
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02/12/2018