Jiayu Zhou

Artificial Intelligence · International Conference on Machine Learning · 2011–2021

A researcher in the Science corpus: 23 papers; trusts 768 researchers and is trusted by 39 researchers here, as inferred from the citation graph.

Subfields

Artificial Intelligence — 444 citations into it; #5,004 of 35,345 by trust here, #6,193 by citations
Reinforcement Learning — 159 citations into it
Computer Vision and Pattern Recognition — 152 citations into it
Representation & Self-Supervised Learning — 119 citations into it
Computational Theory and Mathematics — 95 citations into it
Computational Mechanics — 80 citations into it; #1,367 of 10,001 by trust here, #1,409 by citations
Optimization & Training — 77 citations into it; #881 of 2,601 by trust here, #1,216 by citations
Molecular Biology — 73 citations into it

Whom Jiayu Zhou trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

Who trusts Jiayu Zhou overall

Papers from Jiayu Zhou's perspective

Ordered by how strongly the researchers Jiayu Zhou trusts endorse each paper. Same corpus, a different order for every researcher.

Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
ImageNet classification with deep convolutional neural networks
Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
Long Short-Term Memory
Gradient-based learning applied to document recognition
Attention is All you Need (Neural Information Processing Systems)
ImageNet: A large-scale hierarchical image database
Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Learning Multiple Layers of Features from Tiny Images
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

Efficient multi-task feature learning with calibration (2014) — 58 citations
Integrating low-rank and group-sparse structures for robust multi-task learning (2011) — 344 citations
Transfer Learning in Deep Reinforcement Learning: A Survey (2020) — 899 citations
Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders (2018) — 189 citations
Asynchronous Multi-task Learning (2016) — 47 citations
Online Multi-Task Learning Framework for Ensemble Forecasting (2017) — 29 citations
Graph convolutional networks for computational drug development and discovery (2019) — 382 citations
Data-Free Knowledge Distillation for Heterogeneous Federated Learning (2021) — 1,012 citations
Federated Adversarial Debiasing for Fair and Transferable Representations (2021) — 68 citations
Ranking Policy Gradient (2019) — 8 citations
MetaPred: Meta-Learning for Clinical Risk Prediction with Limited Patient Electronic Health Records (2019) — 121 citations
Identify Susceptible Locations in Medical Records via Adversarial Attacks on Deep Predictive Models (2018) — 67 citations
Differentially Private Generative Adversarial Network (2018) — 593 citations
Efficient Large-Scale Fleet Management via Multi-Agent Deep Reinforcement Learning (2018) — 386 citations
Patient Subtyping via Time-Aware LSTM Networks (2017) — 702 citations
Privacy-Preserving Distributed Multi-Task Learning with Asynchronous Updates (2017) — 77 citations
Interactive Multi-task Relationship Learning (2016) — 12 citations
Multi-Task Feature Interaction Learning (2016) — 33 citations
GSpartan: a Geospatio-Temporal Multi-task Learning Framework for Multi-location Prediction (2016) — 22 citations
FORMULA: FactORized MUlti-task LeArning for task discovery in personalized medical models (2015) — 33 citations