1 citations · 2 across the 23 of their papers we have counts for
27 papers
Defense Filters for Robust Learning of Partially Observed Dynamical Systems
Jihun Kim, Javad Lavaei
Robust estimation of unknown system dynamics from partial observations under attack is a core challenge in learning for control, increasingly critical in multi-agent networks subje…
A Deficiency-Based Approach for Unbalanced Three-Phase Distribution System Expansion Planning
Eli Brock, Miguel Heleno, Javad Lavaei +1
Distribution planners typically characterize grid needs through power flow studies and fit upgrades to those needs by hand. More principled one-shot optimization methods either do…
Groundability, Not Scale Alone: When Weak Reviewers Can Audit Strong Coding Agents
Junyu Guo, Shangding Gu, Ming Jin +1
Coding agents can return plausible patches that omit required behavior. These failures are hard to review because long traces and confident summaries often hide what was missed. We…
When Context Changes: Understanding Update Failures in LLMs
Junyu Guo, Yuchen Fang, Shangding Gu +3
As preferences, goals, and facts change, LLM agents must use the current state while earlier versions remain in context. Yet they can answer with an old value of the same variable,…
LLMs Should Express Uncertainty Explicitly
Junyu Guo, Shangding Gu, Ming Jin +2
Large language models (LLMs) often produce confident yet incorrect answers, which can lead to risky failures in real-world applications. We study whether post-training can make a m…
Structural Correspondence and Universal Approximation in Diagonal plus Low-Rank Neural Networks
Ying Chen, Aoxi Li, Jihun Kim +1
The massive computational costs of scaling modern deep learning architectures have driven the widespread use of parameter-efficient low-rank structures, such as LoRA and low-rank f…
Huber-based Robust System Identification with Near-Optimal Guarantees Across Independent and Adversarial Regimes
Jihun Kim, Javad Lavaei
Dynamical systems can confront one of two extreme types of disturbances: persistent zero-mean independent noise, and sparse nonzero-mean adversarial attacks, depending on the speci…
A Trust-Region Interior-Point Stochastic Sequential Quadratic Programming Method
Yuchen Fang, Jihun Kim, Sen Na +2
In this paper, we propose a trust-region interior-point stochastic sequential quadratic programming (TR-IP-SSQP) method for solving optimization problems with a stochastic objectiv…
Why is Normalization Preferred? A Worst-Case Complexity Theory for Stochastically Preconditioned SGD under Heavy-Tailed Noise
Yuchen Fang, James Demmel, Javad Lavaei
We develop a worst-case complexity theory for stochastically preconditioned stochastic gradient descent (SPSGD) and its accelerated variants under heavy-tailed noise, a setting tha…
System Identification under Noise and Attack Regimes: Agnostic and Composite Robustness
Jihun Kim, Javad Lavaei
Dynamical systems often confront persistent zero-mean independent noise and/or sparse nonzero-mean adversarial attacks. While mean-based estimators like least-squares handle the fo…
3DGS-TR: Scalable Second-Order Trust-Region Method for 3D Gaussian Splatting
Roger Hsiao, Yuchen Fang, Xiangru Huang +6
We propose 3DGS-TR,a second-order optimizer for accelerating the scene training problem in 3D Gaussian Splatting (3DGS). Unlike existing second-order approaches that rely on ex…
TRSVR: An Adaptive Stochastic Trust-Region Method with Variance Reduction
Yuchen Fang, Xinshou Zheng, Javad Lavaei
We propose a stochastic trust-region method for unconstrained nonconvex optimization that incorporates stochastic variance-reduced gradients (SVRG) to accelerate convergence. Unlik…
All-Pass Fractional OPF: A Solver-Friendly, Physics-Preserving Approximation of AC OPF
Milad Hasanzadeh, Amin Kargarian, Javad Lavaei
This paper presents a fractional approximation of the AC optimal power flow (AC OPF) problem based on an all-pass approximation of the exponential power flow kernel. The classical…
Bridging Batch and Streaming Estimations to System Identification under Adversarial Attacks
Jihun Kim, Javad Lavaei
System identification in modern engineering systems faces emerging challenges from unanticipated adversarial attacks beyond existing detection mechanisms. In this work, we obtain a…
StyleBench: Evaluating thinking styles in Large Language Models
Junyu Guo, Shangding Gu, Ming Jin +2
Structured reasoning can improve the inference performance of large language models (LLMs), but it also introduces computational cost and control constraints. When additional reaso…
Few-Shot Test-Time Optimization Without Retraining for Semiconductor Recipe Generation and Beyond
Shangding Gu, Donghao Ying, Ming Jin +4
We introduce Model Feedback Learning (MFL), a novel test-time optimization framework for optimizing inputs to pre-trained AI models or deployed hardware systems without requiring a…
On the Sharp Input-Output Analysis of Nonlinear Systems under Adversarial Attacks
Jihun Kim, Yuchen Fang, Javad Lavaei
This paper is concerned with learning the input-output mapping of general nonlinear dynamical systems. While the existing literature focuses on Gaussian inputs and benign disturban…
System Identification from Partial Observations under Adversarial Attacks
Jihun Kim, Javad Lavaei
This paper is concerned with the partially observed linear system identification, where the goal is to obtain reasonably accurate estimation of the balanced truncation of the true…
Coordinating Distributed Energy Resources with Nodal Pricing in Distribution Networks: a Game-Theoretic Approach
Eli Brock, Jingqi Li, Javad Lavaei +1
We propose a real-time nodal pricing mechanism for cost minimization and voltage control in a distribution network with autonomous distributed energy resources and analyze the resu…
Subgradient Method for System Identification with Non-Smooth Objectives
Baturalp Yalcin, Jihun Kim, Javad Lavaei
This paper investigates a subgradient-based algorithm to solve the system identification problem for linear time-invariant systems with non-smooth objectives. This is essential for…
Don't Trade Off Safety: Diffusion Regularization for Constrained Offline RL
Junyu Guo, Zhi Zheng, Donghao Ying +4
Constrained reinforcement learning (RL) seeks high-performance policies under safety constraints. We focus on an offline setting where the agent has only a fixed dataset -- common…
Distributionally Robust Joint Chance-Constrained Optimal Power Flow using Relative Entropy
Eli Brock, Haixiang Zhang, Javad Lavaei +1
Designing robust algorithms for the optimal power flow (OPF) problem is critical for the control of large-scale power systems under uncertainty. The chance-constrained OPF (CCOPF)…
Online Bandit Nonlinear Control with Dynamic Batch Length and Adaptive Learning Rate
Jihun Kim, Javad Lavaei
This paper is concerned with the online bandit nonlinear control, which aims to learn the best stabilizing controller from a pool of stabilizing and destabilizing controllers of un…
Prevailing against Adversarial Noncentral Disturbances: Exact Recovery of Linear Systems with the -norm Estimator
Jihun Kim, Javad Lavaei
This paper studies the linear system identification problem in the general case where the disturbance is sub-Gaussian, correlated, and possibly adversarial. First, we consider the…