research
∙
08/31/2023
Transformers as Support Vector Machines
Since its inception in "Attention Is All You Need", transformer architec...
share
research
∙
06/23/2023
Max-Margin Token Selection in Attention Mechanism
Attention mechanism is a central component of the transformer architectu...
research
∙
06/02/2023
Federated Multi-Sequence Stochastic Approximation with Local Hypergradient Estimation
Stochastic approximation with multiple coupled sequences (MSA) has found...
research
∙
11/08/2022
A Penalty Based Method for Communication-Efficient Decentralized Bilevel Programming
Bilevel programming has recently received attention in the literature, d...
research
∙
07/06/2022
Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods
Online optimization is a well-established optimization paradigm that aim...
research
∙
05/04/2022
FEDNEST: Federated Bilevel, Minimax, and Compositional Optimization
Standard federated optimization methods successfully apply to stochastic...
research
∙
12/09/2021
Fair Structure Learning in Heterogeneous Graphical Models
Inference of community structure in probabilistic graphical models may n...
research
∙
11/13/2021
Identification and Adaptive Control of Markov Jump Systems: Sample Complexity and Regret Bounds
Learning how to effectively control unknown dynamical systems is crucial...
research
∙
05/26/2021
Certainty Equivalent Quadratic Control for Markov Jump Systems
Real-world control applications often involve complex dynamics subject t...
research
∙
04/26/2021
Solving a class of non-convex min-max games using adaptive momentum methods
Adaptive momentum methods have recently attracted a lot of attention for...
research
∙
05/19/2020
Adaptive First-and Zeroth-order Methods for Weakly Convex Stochastic Optimization Problems
In this paper, we design and analyze a new family of adaptive subgradien...
research
∙
11/24/2019
Regularized and Smooth Double Core Tensor Factorization for Heterogeneous Data
We introduce a general tensor model suitable for data analytic tasks for...
research
∙
05/17/2019
Online Distributed Estimation of Principal Eigenspaces
Principal components analysis (PCA) is a widely used dimension reduction...
research
∙
01/25/2019
