Tianyi Chen

Space-time scheduling for green data center networks

2016

This paper puts forward a systematic approach to designing energy-aware traffic-efficient geographical load balancing schemes for data-center networks that are not only optimal, but also computationally efficient and amenable to distributed implementation. Under a stochastic …

Random Feature-based Online Multi-kernel Learning in Environments with Unknown Dynamics

2017 · arXiv (Cornell University)

Kernel-based methods exhibit well-documented performance in various nonlinear learning tasks. Most of them rely on a preselected kernel, whose prudent choice presumes task-specific prior information. Especially when the latter is not available, multi-kernel learning has …

CADA: Communication-Adaptive Distributed Adam

2020 · arXiv (Cornell University)

Stochastic gradient descent (SGD) has taken the stage as the primary workhorse for large-scale machine learning. It is often used with its adaptive variants such as AdaGrad, Adam, and AMSGrad. This paper proposes an adaptive …

Why theoretical photovoltaic suitability does not fully predict deployment: interpretable deep learning of urban-scale siting across Chinese cities

2026 · Applied Energy

Macro-scale photovoltaic (PV) siting studies usually estimate where PV should be built, but rarely test whether theoretical suitability surfaces correspond to where PV is actually deployed. This study addresses that gap by first comparing reconstructed …