43 citations · 52 across the 10 of their papers we have counts for
10 papers
Graph-based Target Back-Propagation for Context Adaptation in Multi-LLM Agentic Systems
Tan Zhu, Tong Yao, Kananart Kuwaranancharoen +4
Context adaptation automates prompt engineering in LLM-based systems by iteratively revising tunable prompts from task feedback, without modifying model weights. Extending this par…
The Serial Scaling Hypothesis
Yuxi Liu, Konpat Preechakul, Kananart Kuwaranancharoen +1
While machine learning has advanced through massive parallelization, we identify a critical blind spot: some problems are fundamentally sequential. These "inherently serial" proble…
Scalable Distributed Optimization of Multi-Dimensional Functions Despite Byzantine Adversaries
Kananart Kuwaranancharoen, Lei Xin, Shreyas Sundaram
The problem of distributed optimization requires a group of networked agents to compute a parameter that minimizes the average of their local cost functions. While there are a vari…
The Minimizer of the Sum of Two Strongly Convex Functions
Kananart Kuwaranancharoen, Shreyas Sundaram
The optimization problem concerning the determination of the minimizer for the sum of convex functions holds significant importance in the realm of distributed and decentralized op…
On the Geometric Convergence of Byzantine-Resilient Distributed Optimization Algorithms
Kananart Kuwaranancharoen, Shreyas Sundaram
The problem of designing distributed optimization algorithms that are resilient to Byzantine adversaries has received significant attention. For the Byzantine-resilient distributed…
On the Benefits of Leveraging Structural Information in Planning Over the Learned Model
Jiajun Shen, Kananart Kuwaranancharoen, Raid Ayoub +2
Model-based Reinforcement Learning (RL) integrates learning and planning and has received increasing attention in recent years. However, learning the model can incur a significant…
On the Conditional Expectation of Mean Shifted Gaussian Distributions
Kananart Kuwaranancharoen
In this paper, we consider a property of univariate Gaussian distributions namely conditional expectation shift (or centroid shift). Specifically, we compare two Gaussian distribut…
On the Set of Possible Minimizers of a Sum of Known and Unknown Functions
Kananart Kuwaranancharoen, Shreyas Sundaram
The problem of finding the minimizer of a sum of convex functions is central to the field of optimization. Thus, it is of interest to understand how that minimizer is related to th…
Byzantine-Resilient Distributed Optimization of Multi-Dimensional Functions
Kananart Kuwaranancharoen, Lei Xin, Shreyas Sundaram
The problem of distributed optimization requires a group of agents to reach agreement on a parameter that minimizes the average of their local cost functions using information rece…
On the Location of the Minimizer of the Sum of Two Strongly Convex Functions
Kananart Kuwaranancharoen, Shreyas Sundaram
The problem of finding the minimizer of a sum of convex functions is central to the field of distributed optimization. Thus, it is of interest to understand how that minimizer is r…