activity
20192026
most citedNeurIPS 2020 Competition: Predicting Generalization in Deep Learning

22 citations · 24 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI2026

Heterogeneous Computing: The Key to Powering the Future of AI Agent Inference

Yiren Zhao, Junyi Liu

AI agent inference is driving an inference heavy datacenter future and exposes bottlenecks beyond compute - especially memory capacity, memory bandwidth and high-speed interconnect…

cs.DB2026

UTune: Towards Uncertainty-Aware Online Index Tuning

Chenning Wu, Sifan Chen, Wentao Wu +4

There have been a flurry of recent proposals on learned benefit estimators for index tuning. Although these learned estimators show promising improvement over what-if query optimiz…

cs.CY20242 cited

Evaluating Generative AI Systems is a Social Science Measurement Challenge

Hanna Wallach, Meera Desai, Nicholas Pangakis +17

Across academia, industry, and government, there is an increasing awareness that the measurement tasks involved in evaluating generative AI (GenAI) systems are especially difficult…

cs.LG202022 cited

NeurIPS 2020 Competition: Predicting Generalization in Deep Learning

Yiding Jiang, Pierre Foret, Scott Yak +7

Understanding generalization in deep learning is arguably one of the most important questions in deep learning. Deep learning has been successfully adopted to a large number of pro…

cs.SE2019

Checking Observational Purity of Procedures

Himanshu Arora, Raghavan Komondoor, G. Ramalingam

Verifying whether a procedure is observationally pure is useful in many software engineering scenarios. An observationally pure procedure always returns the same value for the same…