3 citations · 3 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…
Causal Influences over Social Learning Networks
Mert Kayaalp, Ali H. Sayed
This paper investigates causal influences between agents linked by a social graph and interacting over time. In particular, the work examines the dynamics of social learning models…
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…
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…
Non-Asymptotic Performance of Social Machine Learning Under Limited Data
Ping Hu, Virginia Bordignon, Mert Kayaalp +1
This paper studies the probability of error associated with the social machine learning framework, which involves an independent training phase followed by a cooperative decision-m…