1 citations · 2 across the 23 of their papers we have counts for
13 papers · 1 filter
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…