Wei Wen

Orcid: 0000-0003-0027-4821

Affiliations:
  • Meta Platforms Inc, Menlo Park, USA


According to our database1, Wei Wen authored at least 52 papers between 2015 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2025
Towards Automated Model Design on Recommender Systems.
Trans. Recomm. Syst., September, 2025

2024
InterFormer: Towards Effective Heterogeneous Interaction Learning for Click-Through Rate Prediction.
CoRR, 2024

CubicML: Automated ML for Large ML Systems Co-design with ML Prediction of Performance.
CoRR, 2024

AutoML for Large Capacity Modeling of Meta's Ranking Systems.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

SiGeo: Sub-One-Shot NAS via Geometry of Loss Landscape.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

DistDNAS: Search Efficient Feature Interactions within 2 Hours.
Proceedings of the IEEE International Conference on Big Data, 2024

2023
SiGeo: Sub-One-Shot NAS via Information Theory and Geometry of Loss Landscape.
CoRR, 2023

Farthest Greedy Path Sampling for Two-shot Recommender Search.
CoRR, 2023

NASRec: Weight Sharing Neural Architecture Search for Recommender Systems.
Proceedings of the ACM Web Conference 2023, 2023

2020
AutoGrow: Automatic Layer Growing in Deep Convolutional Networks.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

TRP: Trained Rank Pruning for Efficient Deep Neural Networks.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures.
Proceedings of the 8th International Conference on Learning Representations, 2020

Neural Predictor for Neural Architecture Search.
Proceedings of the Computer Vision - ECCV 2020, 2020

Learning Low-rank Deep Neural Networks via Singular Vector Orthogonality Regularization and Singular Value Sparsification.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Conditional Transferring Features: Scaling GANs to Thousands of Classes with 30% Less High-quality Data for Training.
CoRR, 2019

Joint Pruning on Activations and Weights for Efficient Neural Networks.
CoRR, 2019

AutoGrow: Automatic Layer Growing in Deep Convolutional Networks.
CoRR, 2019

Trained Rank Pruning for Efficient Deep Neural Networks.
Proceedings of the Fifth Workshop on Energy Efficient Machine Learning and Cognitive Computing, 2019

Joint Regularization on Activations and Weights for Efficient Neural Network Pruning.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

How to Obtain and Run Light and Efficient Deep Learning Networks.
Proceedings of the International Conference on Computer-Aided Design, 2019

Learning Efficient Sparse Structures in Speech Recognition.
Proceedings of the IEEE International Conference on Acoustics, 2019

Feature Space Perturbations Yield More Transferable Adversarial Examples.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Exploration of Automatic Mixed-Precision Search for Deep Neural Networks.
Proceedings of the IEEE International Conference on Artificial Intelligence Circuits and Systems, 2019

2018
Neuromorphic computing's yesterday, today, and tomorrow - an evolutional view.
Integr., 2018

Trained Rank Pruning for Efficient Deep Neural Networks.
CoRR, 2018

SmoothOut: Smoothing Out Sharp Minima for Generalization in Large-Batch Deep Learning.
CoRR, 2018

Learning Intrinsic Sparse Structures within Long Short-Term Memory.
Proceedings of the 6th International Conference on Learning Representations, 2018

Neu-NoC: A high-efficient interconnection network for accelerated neuromorphic systems.
Proceedings of the 23rd Asia and South Pacific Design Automation Conference, 2018

Running sparse and low-precision neural network: When algorithm meets hardware.
Proceedings of the 23rd Asia and South Pacific Design Automation Conference, 2018

2017
Learning Intrinsic Sparse Structures within Long Short-term Memory.
CoRR, 2017

Group Scissor: Scaling Neuromorphic Computing Design to Big Neural Networks.
CoRR, 2017

A quantization-aware regularized learning method in multilevel memristor-based neuromorphic computing system.
Proceedings of the IEEE 6th Non-Volatile Memory Systems and Applications Symposium, 2017

TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Faster CNNs with Direct Sparse Convolutions and Guided Pruning.
Proceedings of the 5th International Conference on Learning Representations, 2017

Coordinating Filters for Faster Deep Neural Networks.
Proceedings of the IEEE International Conference on Computer Vision, 2017

MeDNN: A distributed mobile system with enhanced partition and deployment for large-scale DNNs.
Proceedings of the 2017 IEEE/ACM International Conference on Computer-Aided Design, 2017

An FPGA Design Framework for CNN Sparsification and Acceleration.
Proceedings of the 25th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2017

Understanding the design of IBM neurosynaptic system and its tradeoffs: A user perspective.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2017

Group Scissor: Scaling Neuromorphic Computing Design to Large Neural Networks.
Proceedings of the 54th Annual Design Automation Conference, 2017

A Compact DNN: Approaching GoogLeNet-Level Accuracy of Classification and Domain Adaptation.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Classification accuracy improvement for neuromorphic computing systems with one-level precision synapses.
Proceedings of the 22nd Asia and South Pacific Design Automation Conference, 2017

2016
Leveraging Stochastic Memristor Devices in Neuromorphic Hardware Systems.
IEEE J. Emerg. Sel. Topics Circuits Syst., 2016

Holistic SparseCNN: Forging the Trident of Accuracy, Speed, and Size.
CoRR, 2016

Learning Structured Sparsity in Deep Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Exploring the optimal learning technique for IBM TrueNorth platform to overcome quantization loss.
Proceedings of the IEEE/ACM International Symposium on Nanoscale Architectures, 2016

A new learning method for inference accuracy, core occupation, and performance co-optimization on TrueNorth chip.
Proceedings of the 53rd Annual Design Automation Conference, 2016

Thermal optimization for memristor-based hybrid neuromorphic computing systems.
Proceedings of the 21st Asia and South Pacific Design Automation Conference, 2016

2015
Hardware acceleration for neuromorphic computing: An evolving view.
Proceedings of the 15th Non-Volatile Memory Technology Symposium, 2015

A Novel True Random Number Generator Design Leveraging Emerging Memristor Technology.
Proceedings of the 25th edition on Great Lakes Symposium on VLSI, GLVLSI 2015, Pittsburgh, PA, USA, May 20, 2015

EDA Challenges for Memristor-Crossbar based Neuromorphic Computing.
Proceedings of the 25th edition on Great Lakes Symposium on VLSI, GLVLSI 2015, Pittsburgh, PA, USA, May 20, 2015

An EDA framework for large scale hybrid neuromorphic computing systems.
Proceedings of the 52nd Annual Design Automation Conference, 2015


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