Joseph E. Gonzalez

research

∙ 08/06/2023

Leveraging Cloud Computing to Make Autonomous Vehicles Safer

The safety of autonomous vehicles (AVs) depends on their ability to perf...

0 Peter Schafhalter, et al. ∙

research

∙ 05/25/2023

Diversify Your Vision Datasets with Automatic Diffusion-Based Augmentation

Many fine-grained classification tasks, like rare animal identification,...

0 Lisa Dunlap, et al. ∙

research

∙ 05/24/2023

Gorilla: Large Language Model Connected with Massive APIs

Large Language Models (LLMs) have seen an impressive wave of advances re...

0 Shishir G. Patil, et al. ∙

research

∙ 05/24/2023

Decomposing Complex Queries for Tip-of-the-tongue Retrieval

When re-finding items, users who forget or are uncertain about identifyi...

5 Kevin Lin, et al. ∙

research

∙ 05/11/2023

Simple Token-Level Confidence Improves Caption Correctness

The ability to judge whether a caption correctly describes an image is a...

0 Suzanne Petryk, et al. ∙

research

∙ 03/13/2023

FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU

The high computational and memory requirements of large language model (...

0 Ying Sheng, et al. ∙

research

∙ 02/10/2023

The Wisdom of Hindsight Makes Language Models Better Instruction Followers

Reinforcement learning has seen wide success in finetuning large languag...

0 Tianjun Zhang, et al. ∙

research

∙ 11/21/2022

TEMPERA: Test-Time Prompting via Reinforcement Learning

Careful prompt design is critical to the use of large language models in...

0 Tianjun Zhang, et al. ∙

research

∙ 11/21/2022

Multitask Vision-Language Prompt Tuning

Prompt Tuning, conditioning on task-specific learned prompt vectors, has...

0 Sheng Shen, et al. ∙

research

∙ 10/18/2022

Using Language to Extend to Unseen Domains

It is expensive to collect training data for every possible domain that ...

3 Lisa Dunlap, et al. ∙

research

∙ 10/13/2022

Skyplane: Optimizing Transfer Cost and Throughput Using Cloud-Aware Overlays

Cloud applications are increasingly distributing data across multiple re...

0 Paras Jain, et al. ∙

research

∙ 08/19/2022

Spectral Decomposition Representation for Reinforcement Learning

Representation learning often plays a critical role in reinforcement lea...

6 Tongzheng Ren, et al. ∙

research

∙ 07/16/2022

Autonomously Untangling Long Cables

Cables are ubiquitous in many settings and it is often useful to untangl...

10 Vainavi Viswanath, et al. ∙

research

∙ 07/15/2022

POET: Training Neural Networks on Tiny Devices with Integrated Rematerialization and Paging

Fine-tuning models on edge devices like mobile phones would enable priva...

10 Shishir G. Patil, et al. ∙

research

∙ 07/14/2022

Making Linear MDPs Practical via Contrastive Representation Learning

It is common to address the curse of dimensionality in Markov decision p...

3 Tianjun Zhang, et al. ∙

research

∙ 06/12/2022

Neurotoxin: Durable Backdoors in Federated Learning

Due to their decentralized nature, federated learning (FL) systems have ...

0 Zhengming Zhang, et al. ∙

research

∙ 05/14/2022

The Sky Above The Clouds

Technology ecosystems often undergo significant transformations as they ...

0 Sarah Chasins, et al. ∙

research

∙ 03/09/2022

All You Need is LUV: Unsupervised Collection of Labeled Images using Invisible UV Fluorescent Indicators

Large-scale semantic image annotation is a significant challenge for lea...

7 Brijen Thananjeyan, et al. ∙

research

∙ 02/06/2022

Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data

The search for effective and robust generalization metrics has been the ...

3 Yaoqing Yang, et al. ∙

research

∙ 01/21/2022

Representing Long-Range Context for Graph Neural Networks with Global Attention

Graph neural networks are powerful architectures for structured datasets...

2 Zhanghao Wu, et al. ∙

research

∙ 12/17/2021

Data Efficient Language-supervised Zero-shot Recognition with Optimal Transport Distillation

Traditional computer vision models are trained to predict a fixed set of...

11 Bichen Wu, et al. ∙

research

∙ 12/08/2021

The Effect of Model Size on Worst-Group Generalization

Overparameterization is shown to result in poor test accuracy on rare su...

4 Alan Pham, et al. ∙

research

∙ 12/02/2021

Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL

Meta-reinforcement learning (meta-RL) has proven to be a successful fram...

0 Charles Packer, et al. ∙

research

∙ 11/05/2021

Grounded Graph Decoding Improves Compositional Generalization in Question Answering

Question answering models struggle to generalize to novel compositions o...

16 Yu Gai, et al. ∙

research

∙ 10/22/2021

C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks

Goal-conditioned reinforcement learning (RL) can solve tasks in a wide r...

0 Tianjun Zhang, et al. ∙

research

∙ 07/23/2021

Taxonomizing local versus global structure in neural network loss landscapes

Viewing neural network models in terms of their loss landscapes has a lo...

9 Yaoqing Yang, et al. ∙

research

∙ 07/22/2021

Accelerating Quadratic Optimization with Reinforcement Learning

First-order methods for quadratic optimization such as OSQP are widely u...

10 Jeffrey Ichnowski, et al. ∙

research

∙ 07/10/2021

LS3: Latent Space Safe Sets for Long-Horizon Visuomotor Control of Iterative Tasks

Reinforcement learning (RL) algorithms have shown impressive success in ...

21 Albert Wilcox, et al. ∙

research

∙ 06/29/2021

Untangling Dense Non-Planar Knots by Learning Manipulation Features and Recovery Policies

Robot manipulation for untangling 1D deformable structures such as ropes...

0 Priya Sundaresan, et al. ∙

research

∙ 06/19/2021

Learning Space Partitions for Path Planning

Path planning, the problem of efficiently discovering high-reward trajec...

5 Kevin Yang, et al. ∙

research

∙ 06/14/2021

CathAI: Fully Automated Interpretation of Coronary Angiograms Using Neural Networks

Coronary heart disease (CHD) is the leading cause of adult death in the ...

1 Robert Avram, et al. ∙

research

∙ 06/11/2021

Online Learning of Competitive Equilibria in Exchange Economies

The sharing of scarce resources among multiple rational agents is one of...

2 Wenshuo Guo, et al. ∙

research

∙ 06/06/2021

PAC Best Arm Identification Under a Deadline

We study (ϵ, δ)-PAC best arm identification, where a decision-maker must...

2 Brijen Thananjeyan, et al. ∙

research

∙ 06/04/2021

Disentangling Dense Multi-Cable Knots

Disentangling two or more cables requires many steps to remove crossings...

7 Vainavi Viswanath, et al. ∙

research

∙ 06/02/2021

Transformers are Deep Infinite-Dimensional Non-Mercer Binary Kernel Machines

Despite their ubiquity in core AI fields like natural language processin...

0 Matthew A. Wright, et al. ∙

research

∙ 04/29/2021

ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training

The increasing size of neural network models has been critical for impro...

13 Jianfei Chen, et al. ∙

research

∙ 04/21/2021

Contingencies from Observations: Tractable Contingency Planning with Learned Behavior Models

Humans have a remarkable ability to make decisions by accurately reasoni...

0 Nicholas Rhinehart, et al. ∙

research

∙ 04/18/2021

Data-Efficient Language-Supervised Zero-Shot Learning with Self-Distillation

Traditional computer vision models are trained to predict a fixed set of...

0 Ruizhe Cheng, et al. ∙

research

∙ 04/16/2021

Pylot: A Modular Platform for Exploring Latency-Accuracy Tradeoffs in Autonomous Vehicles

We present Pylot, a platform for autonomous vehicle (AV) research and de...

0 Ionel Gog, et al. ∙

research

∙ 03/03/2021

Enhancing the Interactivity of Dataframe Queries by Leveraging Think Time

We propose opportunistic evaluation, a framework for accelerating intera...

0 Doris Xin, et al. ∙

research

∙ 12/15/2020

Online Learning Demands in Max-min Fairness

We describe mechanisms for the allocation of a scarce resource among mul...

5 Kirthevasan Kandasamy, et al. ∙

research

∙ 11/12/2020

Intermittent Visual Servoing: Efficiently Learning Policies Robust to Instrument Changes for High-precision Surgical Manipulation

Automation of surgical tasks using cable-driven robots is challenging du...

0 Samuel Paradis, et al. ∙

research

∙ 11/10/2020

Untangling Dense Knots by Learning Task-Relevant Keypoints

Untangling ropes, wires, and cables is a challenging task for robots due...

4 Jennifer Grannen, et al. ∙

research

∙ 10/31/2020

Resource Allocation in Multi-armed Bandit Exploration: Overcoming Nonlinear Scaling with Adaptive Parallelism

We study exploration in stochastic multi-armed bandits when we have acce...

11 Brijen Thananjeyan, et al. ∙

research

∙ 10/29/2020

Recovery RL: Safe Reinforcement Learning with Learned Recovery Zones

Safety remains a central obstacle preventing widespread use of RL in the...

15 Brijen Thananjeyan, et al. ∙

research

∙ 10/27/2020

A Statistical Framework for Low-bitwidth Training of Deep Neural Networks

Fully quantized training (FQT), which uses low-bitwidth hardware by quan...

0 Jianfei Chen, et al. ∙

research

∙ 10/09/2020

MMGSD: Multi-Modal Gaussian Shape Descriptors for Correspondence Matching in 1D and 2D Deformable Objects

We explore learning pixelwise correspondences between images of deformab...

1 Aditya Ganapathi, et al. ∙

research

∙ 10/04/2020

Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting

The goal of continual learning (CL) is to learn a sequence of tasks with...

9 Sayna Ebrahimi, et al. ∙

research

∙ 09/01/2020

A Review of Single-Source Deep Unsupervised Visual Domain Adaptation

Large-scale labeled training datasets have enabled deep neural networks ...

7 Sicheng Zhao, et al. ∙

research

∙ 08/26/2020

Benchmarking Semi-supervised Federated Learning

Federated learning promises to use the computational power of edge devic...

15 Zhengming Zhang, et al. ∙

Joseph E. Gonzalez

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