Siyu Wang | DeepAI

AI Chat

Featured Co-authors

Jun Zhu
239 publications
Bo Zhang
226 publications
Yong Li
127 publications
Julian McAuley
120 publications
Lina Yao
99 publications
Jun Yang
88 publications
Wei Lin
74 publications
Quan Z. Sheng
51 publications
Chongxuan Li
43 publications
Dietmar Jannach
40 publications
Shiwei Zhang
37 publications

∙ 09/13/2023

GPU Scheduler for De Novo Genome Assembly with Multiple MPI Processes

De Novo Genome assembly is one of the most important tasks in computatio...

0 Minhao Li, et al. ∙

∙ 08/22/2023

On the Opportunities and Challenges of Offline Reinforcement Learning for Recommender Systems

Reinforcement learning serves as a potent tool for modeling dynamic user...

0 Xiaocong Chen, et al. ∙

∙ 04/17/2023

Causal Disentangled Variational Auto-Encoder for Preference Understanding in Recommendation

Recommendation models are typically trained on observational user intera...

0 Siyu Wang, et al. ∙

∙ 04/17/2023

Causal Decision Transformer for Recommender Systems via Offline Reinforcement Learning

Reinforcement learning-based recommender systems have recently gained po...

0 Siyu Wang, et al. ∙

∙ 03/03/2023

Ada-Grouper: Accelerating Pipeline Parallelism in Preempted Network by Adaptive Group-Scheduling for Micro-Batches

Pipeline parallelism has been demonstrated to be a remarkable approach t...

0 Siyu Wang, et al. ∙

∙ 02/16/2023

Auto-Parallelizing Large Models with Rhino: A Systematic Approach on Production AI Platform

We present Rhino, a system for accelerating tensor programs with automat...

0 Shiwei Zhang, et al. ∙

∙ 02/13/2023

Expediting Distributed DNN Training with Device Topology-Aware Graph Deployment

This paper presents TAG, an automatic system to derive optimized DNN tra...

0 Shiwei Zhang, et al. ∙

∙ 09/26/2022

Optimizing DNN Compilation for Distributed Training with Joint OP and Tensor Fusion

This paper proposes DisCo, an automatic deep learning compilation module...

0 Xiaodong Yi, et al. ∙

∙ 09/17/2022

Intrinsically Motivated Reinforcement Learning based Recommendation with Counterfactual Data Augmentation

Deep reinforcement learning (DRL) has been proven its efficiency in capt...

0 Xiaocong Chen, et al. ∙

∙ 08/10/2022

Deep Reinforcement Learning for Dynamic Recommendation with Model-agnostic Counterfactual Policy Synthesis

Recent advances in recommender systems have proved the potential of Rein...

0 Siyu Wang, et al. ∙

∙ 06/17/2022

Fast Lossless Neural Compression with Integer-Only Discrete Flows

By applying entropy codecs with learned data distributions, neural compr...

0 Siyu Wang, et al. ∙

∙ 04/01/2022

Model-agnostic Counterfactual Synthesis Policy for Interactive Recommendation

Interactive recommendation is able to learn from the interactive process...

0 Siyu Wang, et al. ∙

∙ 12/02/2021

Adversarial Robustness of Deep Reinforcement Learning based Dynamic Recommender Systems

Adversarial attacks, e.g., adversarial perturbations of the input and ad...

0 Siyu Wang, et al. ∙

∙ 07/08/2020

Auto-MAP: A DQN Framework for Exploring Distributed Execution Plans for DNN Workloads

The last decade has witnessed growth in the computational requirements f...

34 Siyu Wang, et al. ∙

∙ 07/02/2020

DAPPLE: A Pipelined Data Parallel Approach for Training Large Models

It is a challenging task to train large DNN models on sophisticated GPU ...

1 Shiqing Fan, et al. ∙

∙ 06/01/2020

Streaming Language Identification using Combination of Acoustic Representations and ASR Hypotheses

This paper presents our modeling and architecture approaches for buildin...

0 Chander Chandak, et al. ∙

∙ 04/02/2019

Curls & Whey: Boosting Black-Box Adversarial Attacks

Image classifiers based on deep neural networks suffer from harassment c...

20 Yucheng Shi, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world