4 citations · 4 across the 4 of their papers we have counts for
9 papers
Test-Time Collaborative Classification over Multi-Agent Networks
Ping Hu, Mert Kayaalp, Ali H. Sayed
The increasing heterogeneity of multi-agent systems poses significant challenges for jointly training a global model across agents. At the same time, cooperative inference between…
Signal Recovery from Time and Frequency Samples
Mert Kayaalp, Oleg Szehr
We analyze signal recovery when samples are taken concomitantly from a signal and its Fourier transform. This two-sided sampling framework extends classical one-sided reconstructio…
Opinion Consensus Formation Among Networked Large Language Models
Iris Yazici, Mert Kayaalp, Stefan Taga +1
Can classical consensus models predict the group behavior of large language models (LLMs)? We examine multi-round interactions among LLM agents through the DeGroot framework, where…
Test-Time Efficient Pretrained Model Portfolios for Time Series Forecasting
Mert Kayaalp, Caner Turkmen, Oleksandr Shchur +4
Is bigger always better for time series foundation models? With the question in mind, we explore an alternative to training a single, large monolithic model: building a portfolio o…
Causal Influence in Federated Edge Inference
Mert Kayaalp, Yunus Inan, Visa Koivunen +1
In this paper, we consider a setting where heterogeneous agents with connectivity are performing inference using unlabeled streaming data. Observed data are only partially informat…
Detection of Malicious Agents in Social Learning
Valentina Shumovskaia, Mert Kayaalp, Ali H. Sayed
Non-Bayesian social learning is a framework for distributed hypothesis testing aimed at learning the true state of the environment. Traditionally, the agents are assumed to receive…