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05/05/2023
COLA: How to adapt vision-language models to Compose Objects Localized with Attributes?
Compositional reasoning is a hallmark of human visual intelligence; yet ...
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05/27/2022
Private and Byzantine-Proof Cooperative Decision-Making
The cooperative bandit problem is a multi-agent decision problem involvi...
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05/27/2022
Neural Basis Models for Interpretability
Due to the widespread use of complex machine learning models in real-wor...
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05/27/2022
Scalable Interpretability via Polynomials
Generalized Additive Models (GAMs) have quickly become the leading choic...
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12/09/2021
Adaptive Methods for Aggregated Domain Generalization
Domain generalization involves learning a classifier from a heterogeneou...
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11/24/2021
One More Step Towards Reality: Cooperative Bandits with Imperfect Communication
The cooperative bandit problem is increasingly becoming relevant due to ...
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08/17/2021
Social influence leads to the formation of diverse local trends
How does the visual design of digital platforms impact user behavior and...
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03/29/2021
Adaptive Methods for Real-World Domain Generalization
Invariant approaches have been remarkably successful in tackling the pro...
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03/08/2021
Provably Efficient Cooperative Multi-Agent Reinforcement Learning with Function Approximation
Reinforcement learning in cooperative multi-agent settings has recently ...
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02/24/2021
No-Regret Algorithms for Private Gaussian Process Bandit Optimization
The widespread proliferation of data-driven decision-making has ushered ...
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10/22/2020
Differentially-Private Federated Linear Bandits
The rapid proliferation of decentralized learning systems mandates the n...
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08/14/2020
Cooperative Multi-Agent Bandits with Heavy Tails
We study the heavy-tailed stochastic bandit problem in the cooperative m...
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08/14/2020
Kernel Methods for Cooperative Multi-Agent Contextual Bandits
Cooperative multi-agent decision making involves a group of agents coope...
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08/29/2019
Smaller Models, Better Generalization
Reducing network complexity has been a major research focus in recent ye...
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07/08/2019
Thompson Sampling on Symmetric α-Stable Bandits
Thompson Sampling provides an efficient technique to introduce prior kno...
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03/05/2019
Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search
A plethora of recent work has shown that convolutional networks are not ...
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02/16/2019
Communication Topologies Between Learning Agents in Deep Reinforcement Learning
A common technique to improve speed and robustness of learning in deep r...
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12/27/2018
Evaluating Generative Adversarial Networks on Explicitly Parameterized Distributions
The true distribution parameterizations of commonly used image datasets ...
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12/08/2018
No Peek: A Survey of private distributed deep learning
We survey distributed deep learning models for training or inference wit...
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11/30/2018
How to Organize your Deep Reinforcement Learning Agents: The Importance of Communication Topology
In this empirical paper, we investigate how learning agents can be arran...
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09/16/2018
Maximum-Entropy Fine-Grained Classification
Fine-Grained Visual Classification (FGVC) is an important computer visio...
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07/25/2018
Coreset-Based Neural Network Compression
We propose a novel Convolutional Neural Network (CNN) compression algori...
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03/20/2018
Closing the AI Knowledge Gap
AI researchers employ not only the scientific method, but also methodolo...
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02/14/2018
MemeSequencer: Sparse Matching for Embedding Image Macros
The analysis of the creation, mutation, and propagation of social media ...
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09/22/2017
Modeling Image Virality with Pairwise Spatial Transformer Networks
The study of virality and information diffusion online is a topic gainin...
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05/22/2017
Training with Confusion for Fine-Grained Visual Classification
Research in Fine-Grained Visual Classification has focused on tackling t...
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09/12/2016
Examining Representational Similarity in ConvNets and the Primate Visual Cortex
We compare several ConvNets with different depth and regularization tech...
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08/05/2016