Joseph Gonzalez
25 papers · 2005–2026 · 10 venues · across top CS/AI venues
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Research topics
Machine Learning
(17)
Artificial Intelligence
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Core AI
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Deep Learning
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Optimization & Theory Β· Machine Learning
(7)
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Keywords
model compression
(4)
multi-armed bandit
(3)
resource allocation
(3)
federated learning
(2)
cable untangling
(2)
online learning
(2)
sample efficiency
(1)
belief propagation
(1)
zero-shot learning
(1)
structured prediction
(1)
robotic manipulation
(1)
causal discovery
(1)
object detection
(1)
ai education
(1)
stochastic gradient descent
(1)
syntactic parsing
(1)
question answering
(1)
adversarial machine learning
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semantic parsing
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attention mechanism
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Papers
Model AI Assignments 2026
AAAI 2026
Cloudcast: High-Throughput, Cost-Aware Overlay Multicast in the Cloud
NSDI 2024
Cilantro: Performance-Aware Resource Allocation for General Objectives via Online Feedback
OSDI 2023
Decomposing Complex Queries for Tip-of-the-tongue Retrieval
EMNLP 2023
Context-Aware Streaming Perception in Dynamic Environments
ECCV 2022
Learning Competitive Equilibria in Exchange Economies with Bandit Feedback
AISTATS 2022
Making Linear MDPs Practical via Contrastive Representation Learning
ICML 2022
Neurotoxin: Durable Backdoors in Federated Learning
ICML 2022
On Guiding Visual Attention With Language Specification
CVPR 2022
POET: Training Neural Networks on Tiny Devices with Integrated Rematerialization and Paging
ICML 2022
Reliable Visual Question Answering: Abstain Rather Than Answer Incorrectly
ECCV 2022
ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training
ICML 2021
Contrastive Code Representation Learning
EMNLP 2021
Grounded Graph Decoding improves Compositional Generalization in Question Answering
EMNLP 2021
Resource Allocation in Multi-armed Bandit Exploration: Overcoming Sublinear Scaling with Adaptive Parallelism
ICML 2021
Untangling Dense Non-Planar Knots by Learning Manipulation Features and Recovery Policies
RSS 2021
FetchSGD: Communication-Efficient Federated Learning with Sketching
ICML 2020
Frustratingly Simple Few-Shot Object Detection
ICML 2020
Thompson Sampling for Linearly Constrained Bandits
AISTATS 2020
Untangling Dense Knots by Learning Task-Relevant Keypoints
CoRL 2020
RLlib: Abstractions for Distributed Reinforcement Learning
ICML 2018
Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions
CVPR 2018
Random projection design for scalable implicit smoothing of randomly observed stochastic processes
AISTATS 2017
Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees
AISTATS 2011
Residual Splash for Optimally Parallelizing Belief Propagation
AISTATS 2005