128 citations · 134 across the 8 of their papers we have counts for
8 papers
Do LLMs Recognize Your Latent Preferences? A Benchmark for Latent Information Discovery in Personalized Interaction
Ioannis Tsaknakis, Bingqing Song, Shuyu Gan +5
Large Language Models (LLMs) excel at producing broadly relevant text, but this generality becomes a limitation when user-specific preferences are required, such as recommending re…
Scalable Parameter and Memory Efficient Pretraining for LLM: Recent Algorithmic Advances and Benchmarking
Athanasios Glentis, Jiaxiang Li, Qiulin Shang +4
Fueled by their remarkable ability to tackle diverse tasks across multiple domains, large language models (LLMs) have grown at an unprecedented rate, with some recent models contai…
A Discretization Approach for Bilevel Optimization with Low-Dimensional and Non-Convex Lower-Level
Xiaotian Jiang, Ioannis Tsaknakis, Prashant Khanduri +1
Bilevel optimization (BLO) problem, where two optimization problems (referred to as upper- and lower-level problems) are coupled hierarchically, has wide applications in areas such…
A Doubly Stochastically Perturbed Algorithm for Linearly Constrained Bilevel Optimization
Prashant Khanduri, Ioannis Tsaknakis, Yihua Zhang +2
In this work, we develop analysis and algorithms for a class of (stochastic) bilevel optimization problems whose lower-level (LL) problem is strongly convex and linearly constraine…
An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning
Yihua Zhang, Prashant Khanduri, Ioannis Tsaknakis +3
Recently, bi-level optimization (BLO) has taken center stage in some very exciting developments in the area of signal processing (SP) and machine learning (ML). Roughly speaking, B…
Zeroth-Order SciML: Non-intrusive Integration of Scientific Software with Deep Learning
Ioannis Tsaknakis, Bhavya Kailkhura, Sijia Liu +4
Using deep learning (DL) to accelerate and/or improve scientific workflows can yield discoveries that are otherwise impossible. Unfortunately, DL models have yielded limited succes…
Minimax Problems with Coupled Linear Constraints: Computational Complexity, Duality and Solution Methods
Ioannis Tsaknakis, Mingyi Hong, Shuzhong Zhang
In this work we study a special minimax problem where there are linear constraints that couple both the minimization and maximization decision variables. The problem is a generaliz…
Hybrid Block Successive Approximation for One-Sided Non-Convex Min-Max Problems: Algorithms and Applications
Songtao Lu, Ioannis Tsaknakis, Mingyi Hong +1
The min-max problem, also known as the saddle point problem, is a class of optimization problems which minimizes and maximizes two subsets of variables simultaneously. This class o…