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06/21/2023
Distributed Random Reshuffling Methods with Improved Convergence
This paper proposes two distributed random reshuffling methods, namely G...
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05/07/2023
Text-to-Image Diffusion Models can be Easily Backdoored through Multimodal Data Poisoning
With the help of conditioning mechanisms, the state-of-the-art diffusion...
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03/12/2023
One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale
This paper proposes a unified diffusion framework (dubbed UniDiffuser) t...
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01/30/2023
Distributed Stochastic Optimization under a General Variance Condition
Distributed stochastic optimization has drawn great attention recently d...
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01/14/2023
CEDAS: A Compressed Decentralized Stochastic Gradient Method with Improved Convergence
In this paper, we consider solving the distributed optimization problem ...
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03/29/2022
Alignment-Uniformity aware Representation Learning for Zero-shot Video Classification
Most methods tackle zero-shot video classification by aligning visual-se...
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12/31/2021
Distributed Random Reshuffling over Networks
In this paper, we consider the distributed optimization problem where n ...
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07/26/2021
Provably Accelerated Decentralized Gradient Method Over Unbalanced Directed Graphs
In this work, we consider the decentralized optimization problem in whic...
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06/14/2021
Compressed Gradient Tracking for Decentralized Optimization Over General Directed Networks
In this paper, we propose two communication-efficient algorithms for dec...
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05/11/2021
Improving the Transient Times for Distributed Stochastic Gradient Methods
We consider the distributed optimization problem where n agents each pos...
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03/25/2021
Compressed Gradient Tracking Methods for Decentralized Optimization with Linear Convergence
Communication compression techniques are of growing interests for solvin...
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10/26/2020
Multimodal Topic Learning for Video Recommendation
Facilitated by deep neural networks, video recommendation systems have m...
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09/12/2020
A general framework for decentralized optimization with first-order methods
Decentralized optimization to minimize a finite sum of functions over a ...
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03/31/2020
A Robust Gradient Tracking Method for Distributed Optimization over Directed Networks
In this paper, we consider the problem of distributed consensus optimiza...
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06/28/2019
Asymptotic Network Independence in Distributed Optimization for Machine Learning
We provide a discussion of several recent results which have overcome a ...
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06/06/2019
A Non-Asymptotic Analysis of Network Independence for Distributed Stochastic Gradient Descent
This paper is concerned with minimizing the average of n cost functions ...
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10/15/2018
Push-Pull Gradient Methods for Distributed Optimization in Networks
In this paper, we focus on solving a distributed convex optimization pro...
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10/09/2018
Deep Attentive Tracking via Reciprocative Learning
Visual attention, derived from cognitive neuroscience, facilitates human...
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06/11/2018
Swarming for Faster Convergence in Stochastic Optimization
We study a distributed framework for stochastic optimization which is in...
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05/25/2018
Distributed Stochastic Gradient Tracking Methods
In this paper, we study the problem of distributed multi-agent optimizat...
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03/21/2018
A Distributed Stochastic Gradient Tracking Method
In this paper, we study the problem of distributed multi-agent optimizat...
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03/20/2018