Joseph E Gonzalez
25 papers · 2013–2024 · 4 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (58) π Conference Polyglot Β· Bronze π Academic Marathon Β· Half π Interdisciplinary Bridge Β· Gold π£ Hot Topic Early Bird
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(20)
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(7)
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The Questioner
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Prolific Year Β· Productive
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Century Club Β· Bronze
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(133)
Venues
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Research topics
Machine Learning
(20)
Artificial Intelligence
(12)
Core AI
(10)
Optimization & Theory
(10)
Deep Learning
(8)
Reinforcement Learning
(7)
Application Areas
(7)
Learning Types
(7)
Methods
(6)
Applications
(5)
Models
(5)
Natural Language Processing
(4)
Resources & Methods
(4)
Mathematics & Optimization
(3)
Core Methods
(3)
Keywords
large language model
(4)
reinforcement learning
(2)
sparse reward
(2)
contingency planning
(2)
data augmentation
(2)
neural network
(2)
diffusion model
(2)
prompt engineering
(2)
multi-agent system
(2)
sample efficiency
(1)
domain generalization
(1)
imitation learning
(1)
path planning
(1)
black-box optimization
(1)
double descent
(1)
deep reinforcement learning
(1)
online learning
(1)
distributed learning
(1)
image generation
(1)
code generation
(1)
Papers
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
NeurIPS 2024
CARFF: Conditional Auto-encoded Radiance Field for 3D Scene Forecasting
ECCV 2024
Gorilla: Large Language Model Connected with Massive APIs
NeurIPS 2024
SGLang: Efficient Execution of Structured Language Model Programs
NeurIPS 2024
Stylus: Automatic Adapter Selection for Diffusion Models
NeurIPS 2024
Synthetic Programming Elicitation for Text-to-Code in Very Low-Resource Programming and Formal Languages
NeurIPS 2024
Diversify Your Vision Datasets with Automatic Diffusion-based Augmentation
NeurIPS 2023
Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena
NeurIPS 2023
VCG Mechanism Design with Unknown Agent Values under Stochastic Bandit Feedback
JMLR 2023
Is Anyone There? Learning a Planner Contingent on Perceptual Uncertainty
CoRL 2022
Accelerating Quadratic Optimization with Reinforcement Learning
NeurIPS 2021
Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL
NeurIPS 2021
Learning Space Partitions for Path Planning
NeurIPS 2021
LS3: Latent Space Safe Sets for Long-Horizon Visuomotor Control of Sparse Reward Iterative Tasks
CoRL 2021
MADE: Exploration via Maximizing Deviation from Explored Regions
NeurIPS 2021
NovelD: A Simple yet Effective Exploration Criterion
NeurIPS 2021
Representing Long-Range Context for Graph Neural Networks with Global Attention
NeurIPS 2021
RLlib Flow: Distributed Reinforcement Learning is a Dataflow Problem
NeurIPS 2021
Taxonomizing local versus global structure in neural network loss landscapes
NeurIPS 2021
A Statistical Framework for Low-bitwidth Training of Deep Neural Networks
NeurIPS 2020
Boundary thickness and robustness in learning models
NeurIPS 2020
ANODEV2: A Coupled Neural ODE Framework
NeurIPS 2019
On-Policy Robot Imitation Learning from a Converging Supervisor
CoRL 2019
Parallel Double Greedy Submodular Maximization
NeurIPS 2014
Optimistic Concurrency Control for Distributed Unsupervised Learning
NeurIPS 2013