Search Results for author: Vincent Liu

Found 18 papers, 2 papers with code

Carbon Connect: An Ecosystem for Sustainable Computing

no code implementations22 May 2024 Benjamin C. Lee, David Brooks, Arthur van Benthem, Udit Gupta, Gage Hills, Vincent Liu, Benjamin Pierce, Christopher Stewart, Emma Strubell, Gu-Yeon Wei, Adam Wierman, Yuan YAO, Minlan Yu

For embodied carbon, we must re-think conventional design strategies -- over-provisioned monolithic servers, frequent hardware refresh cycles, custom silicon -- and adopt life-cycle design strategies that more effectively reduce, reuse and recycle hardware at scale.


Measuring and Mitigating Interference in Reinforcement Learning

no code implementations10 Jul 2023 Vincent Liu, Han Wang, Ruo Yu Tao, Khurram Javed, Adam White, Martha White

Lastly, we outline a class of algorithms which we call online-aware that are designed to mitigate interference, and show they do reduce interference according to our measure and that they improve stability and performance in several classic control environments.


Asymptotically Unbiased Off-Policy Policy Evaluation when Reusing Old Data in Nonstationary Environments

no code implementations23 Feb 2023 Vincent Liu, Yash Chandak, Philip Thomas, Martha White

In this work, we consider the off-policy policy evaluation problem for contextual bandits and finite horizon reinforcement learning in the nonstationary setting.

Multi-Armed Bandits regression +2

AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving

2 code implementations22 Feb 2023 Zhuohan Li, Lianmin Zheng, Yinmin Zhong, Vincent Liu, Ying Sheng, Xin Jin, Yanping Huang, Zhifeng Chen, Hao Zhang, Joseph E. Gonzalez, Ion Stoica

Model parallelism is conventionally viewed as a method to scale a single large deep learning model beyond the memory limits of a single device.

DABS: A Domain-Agnostic Benchmark for Self-Supervised Learning

1 code implementation23 Nov 2021 Alex Tamkin, Vincent Liu, Rongfei Lu, Daniel Fein, Colin Schultz, Noah Goodman

Self-supervised learning algorithms, including BERT and SimCLR, have enabled significant strides in fields like natural language processing, computer vision, and speech processing.

Self-Supervised Learning

Performance metrics for intervention-triggering prediction models do not reflect an expected reduction in outcomes from using the model

no code implementations2 Jun 2020 Alejandro Schuler, Aashish Bhardwaj, Vincent Liu

Clinical researchers often select among and evaluate risk prediction models using standard machine learning metrics based on confusion matrices.


Training Recurrent Neural Networks Online by Learning Explicit State Variables

no code implementations ICLR 2020 Somjit Nath, Vincent Liu, Alan Chan, Xin Li, Adam White, Martha White

Recurrent neural networks (RNNs) allow an agent to construct a state-representation from a stream of experience, which is essential in partially observable problems.

Incrementally Learning Functions of the Return

no code implementations5 Jul 2019 Brendan Bennett, Wesley Chung, Muhammad Zaheer, Vincent Liu

Temporal difference methods enable efficient estimation of value functions in reinforcement learning in an incremental fashion, and are of broader interest because they correspond learning as observed in biological systems.

Reinforcement Learning (RL)

Recurrent Control Nets for Deep Reinforcement Learning

no code implementations6 Jan 2019 Vincent Liu, Ademi Adeniji, Nathaniel Lee, Jason Zhao, Mario Srouji

Central Pattern Generators (CPGs) are biological neural circuits capable of producing coordinated rhythmic outputs in the absence of rhythmic input.

reinforcement-learning Reinforcement Learning (RL)

Attribute-aware Collaborative Filtering: Survey and Classification

no code implementations20 Oct 2018 Wen-Hao Chen, Chin-Chi Hsu, Yi-An Lai, Vincent Liu, Mi-Yen Yeh, Shou-De Lin

Attribute-aware CF models aims at rating prediction given not only the historical rating from users to items, but also the information associated with users (e. g. age), items (e. g. price), or even ratings (e. g. rating time).

Attribute Classification +2

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