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05/24/2023
ReSync: Riemannian Subgradient-based Robust Rotation Synchronization
This work presents ReSync, a Riemannian subgradient-based algorithm for ...
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05/23/2023
Revisiting Subgradient Method: Complexity and Convergence Beyond Lipschitz Continuity
The subgradient method is one of the most fundamental algorithmic scheme...
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05/02/2023
LogSpecT: Feasible Graph Learning Model from Stationary Signals with Recovery Guarantees
Graph learning from signals is a core task in Graph Signal Processing (G...
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04/08/2023
Decoder-Only or Encoder-Decoder? Interpreting Language Model as a Regularized Encoder-Decoder
The sequence-to-sequence (seq2seq) task aims at generating the target se...
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03/31/2023
Decentralized Weakly Convex Optimization Over the Stiefel Manifold
We focus on a class of non-smooth optimization problems over the Stiefel...
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03/12/2023
A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data
In this work, we present the Bregman Alternating Projected Gradient (BAP...
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02/23/2023
Testing Stationarity Concepts for ReLU Networks: Hardness, Regularity, and Robust Algorithms
We study the computational problem of the stationarity test for the empi...
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02/09/2023
Outlier-Robust Gromov Wasserstein for Graph Data
Gromov Wasserstein (GW) distance is a powerful tool for comparing and al...
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01/24/2023
A Stability Analysis of Fine-Tuning a Pre-Trained Model
Fine-tuning a pre-trained model (such as BERT, ALBERT, RoBERTa, T5, GPT,...
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12/26/2022
Doubly Smoothed GDA: Global Convergent Algorithm for Constrained Nonconvex-Nonconcave Minimax Optimization
Nonconvex-nonconcave minimax optimization has been the focus of intense ...
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11/28/2022
On the Effectiveness of Parameter-Efficient Fine-Tuning
Fine-tuning pre-trained models has been ubiquitously proven to be effect...
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09/22/2022
Nonsmooth Composite Nonconvex-Concave Minimax Optimization
Nonconvex-concave minimax optimization has received intense interest in ...
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07/15/2022
Riemannian Natural Gradient Methods
This paper studies large-scale optimization problems on Riemannian manif...
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06/11/2022
Convergence and Recovery Guarantees of the K-Subspaces Method for Subspace Clustering
The K-subspaces (KSS) method is a generalization of the K-means method f...
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05/17/2022
Fast and Provably Convergent Algorithms for Gromov-Wasserstein in Graph Learning
In this paper, we study the design and analysis of a class of efficient ...
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02/22/2022
Exact Community Recovery over Signed Graphs
Signed graphs encode similarity and dissimilarity relationships among di...
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01/19/2022
Variance-Reduced Stochastic Quasi-Newton Methods for Decentralized Learning: Part I
In this work, we investigate stochastic quasi-Newton methods for minimiz...
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12/28/2021
Non-Convex Joint Community Detection and Group Synchronization via Generalized Power Method
This paper proposes a Generalized Power Method (GPM) to tackle the probl...
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12/13/2021
Orthogonal Group Synchronization with Incomplete Measurements: Error Bounds and Linear Convergence of the Generalized Power Method
Group synchronization refers to estimating a collection of group element...
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09/30/2021
Accelerating Perturbed Stochastic Iterates in Asynchronous Lock-Free Optimization
We show that stochastic acceleration can be achieved under the perturbed...
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05/25/2021
Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums
The problem of finding near-stationary points in convex optimization has...
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05/12/2021
Learning Graphs from Smooth Signals under Moment Uncertainty
We consider the problem of inferring the graph structure from a given se...
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03/18/2021
Probabilistic Simplex Component Analysis
This study presents PRISM, a probabilistic simplex component analysis ap...
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01/18/2021
Quartic Perturbation-based Outage-constrained Robust Design in Two-hop One-way Relay Networks
In this work, we study a classic robust design problem in two-hop one-wa...
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12/29/2020
A Theoretical Analysis of the Repetition Problem in Text Generation
Text generation tasks, including translation, summarization, language mo...
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10/24/2020
Fast Epigraphical Projection-based Incremental Algorithms for Wasserstein Distributionally Robust Support Vector Machine
Wasserstein Distributionally Robust Optimization (DRO) is concerned with...
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09/16/2020
A Unified Approach to Synchronization Problems over Subgroups of the Orthogonal Group
Given a group 𝒢, the problem of synchronization over the group 𝒢 is a co...
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06/29/2020
Non-Convex Exact Community Recovery in Stochastic Block Model
Learning community structures in graphs that are randomly generated by s...
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06/26/2020
Understanding Notions of Stationarity in Non-Smooth Optimization
Many contemporary applications in signal processing and machine learning...
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05/25/2020
Boosting First-order Methods by Shifting Objective: New Schemes with Faster Worst Case Rates
We propose a new methodology to design first-order methods for unconstra...
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05/05/2020
Manifold Proximal Point Algorithms for Dual Principal Component Pursuit and Orthogonal Dictionary Learning
We consider the problem of maximizing the ℓ_1 norm of a linear map over ...
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11/12/2019
Nonsmooth Optimization over Stiefel Manifold: Riemannian Subgradient Methods
Nonsmooth Riemannian optimization is a still under explored subfield of ...
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10/28/2019
A First-Order Algorithmic Framework for Wasserstein Distributionally Robust Logistic Regression
Wasserstein distance-based distributionally robust optimization (DRO) ha...
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07/26/2019
Incremental Methods for Weakly Convex Optimization
We consider incremental algorithms for solving weakly convex optimizatio...
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07/02/2019
Voting-Based Multi-Agent Reinforcement Learning
The recent success of single-agent reinforcement learning (RL) encourage...
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03/12/2019
An Efficient Augmented Lagrangian Based Method for Constrained Lasso
Variable selection is one of the most important tasks in statistics and ...
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11/02/2018
Proximal Gradient Method for Manifold Optimization
This paper considers manifold optimization problems with nonsmooth and n...
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10/07/2018
A Framework for One-Bit and Constant-Envelope Precoding over Multiuser Massive MISO Channels
Consider the following problem: A multi-antenna base station (BS) sends ...
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09/24/2018
Nonconvex Robust Low-rank Matrix Recovery
In this paper we study the problem of recovering a low-rank matrix from ...
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04/23/2018
Minimum Symbol Error Rate-Based Constant Envelope Precoding for Multiuser Massive MISO Downlink
This paper considers the problem of constant envelope (CE) precoder desi...
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05/31/2016
Scalable and Flexible Multiview MAX-VAR Canonical Correlation Analysis
Generalized canonical correlation analysis (GCCA) aims at finding latent...
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12/11/2015
