Solving Bernoulli Rank-One Bandits with Unimodal Thompson Sampling. - Cindy Trinh; Emilie Kaufmann; Claire Vernade; Richard Combes (ALT, 2020)

MLPerf Mobile Inference Benchmark: Why Mobile AI Benchmarking Is Hard and What to Do About It. - Vijay Janapa Reddi; David Kanter; Peter Mattson; Jared Duke; Thai Nguyen; Ramesh Chukka; Kenneth Shiring; Koan-Sin Tan; Mark Charlebois; William Chou; Mostafa El-Khamy; Jungwook Hong; et al. (CoRR, 2020)

A High Performance, Low Complexity Algorithm for Multi-Player Bandits Without Collision Sensing Information. - Cindy Trinh; Richard Combes (CoRR, 2021)

Towards Optimal Algorithms for Multi-Player Bandits without Collision Sensing Information. - Wei Huang 041; Richard Combes; Cindy Trinh (COLT, 2022)

MLPerf Mobile Inference Benchmark: An Industry-Standard Open-Source Machine Learning Benchmark for On-Device AI. - Vijay Janapa Reddi; David Kanter; Peter Mattson; Jared Duke; Thai Nguyen; Ramesh Chukka; Kenneth Shiring; Koan-Sin Tan; Mark Charlebois; William Chou; Mostafa El-Khamy; Jungwook Hong; et al. (MLSys, 2022)

On the Development of Descriptor-Based Machine Learning Models for Thermodynamic Properties: Part 2 - Applicability Domain and Outliers. - Cindy Trinh; Silvia Lasala; Olivier Herbinet; Dimitrios Meimaroglou (Algorithms, 2023)