Is novelty predictable?
C Fannjiang, J Listgarten - Cold Spring Harbor …, 2024 - cshperspectives.cshlp.org
Machine learning–based design has gained traction in the sciences, most notably in the
design of small molecules, materials, and proteins, with societal applications ranging from …
design of small molecules, materials, and proteins, with societal applications ranging from …
Federated linear contextual bandits
This paper presents a novel federated linear contextual bandits model, where individual
clients face different $ K $-armed stochastic bandits coupled through common global …
clients face different $ K $-armed stochastic bandits coupled through common global …
Experiment planning with function approximation
We study the problem of experiment planning with function approximation in contextual
bandit problems. In settings where there is a significant overhead to deploying adaptive …
bandit problems. In settings where there is a significant overhead to deploying adaptive …
[HTML][HTML] Online learning of energy consumption for navigation of electric vehicles
Energy efficient navigation constitutes an important challenge in electric vehicles, due to
their limited battery capacity. We employ a Bayesian approach to model the energy …
their limited battery capacity. We employ a Bayesian approach to model the energy …
Harnessing the Power of Federated Learning in Federated Contextual Bandits
Federated learning (FL) has demonstrated great potential in revolutionizing distributed
machine learning, and tremendous efforts have been made to extend it beyond the original …
machine learning, and tremendous efforts have been made to extend it beyond the original …
Contextual Bandits with Stage-wise Constraints
We study contextual bandits in the presence of a stage-wise constraint (a constraint at each
round), when the constraint must be satisfied both with high probability and in expectation …
round), when the constraint must be satisfied both with high probability and in expectation …
Neural design for genetic perturbation experiments
A Pacchiano, D Wulsin, RA Barton, L Voloch - arXiv preprint arXiv …, 2022 - arxiv.org
The problem of how to genetically modify cells in order to maximize a certain cellular
phenotype has taken center stage in drug development over the last few years (with, for …
phenotype has taken center stage in drug development over the last few years (with, for …
One policy is enough: Parallel exploration with a single policy is near-optimal for reward-free reinforcement learning
P Cisneros-Velarde, B Lyu… - International …, 2023 - proceedings.mlr.press
Although parallelism has been extensively used in Reinforcement Learning (RL), the
quantitative effects of parallel exploration are not well understood theoretically. We study the …
quantitative effects of parallel exploration are not well understood theoretically. We study the …
Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning
We present the first study on provably efficient randomized exploration in cooperative multi-
agent reinforcement learning (MARL). We propose a unified algorithm framework for …
agent reinforcement learning (MARL). We propose a unified algorithm framework for …
Second Order Bounds for Contextual Bandits with Function Approximation
A Pacchiano - arXiv preprint arXiv:2409.16197, 2024 - arxiv.org
Many works have developed algorithms no-regret algorithms for contextual bandits with
function approximation, where the mean rewards over context-action pairs belongs to a …
function approximation, where the mean rewards over context-action pairs belongs to a …