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Shiwei Liu 0003
Person information
- affiliation: University of Oxford, Mathematical Institute, UK
- affiliation: University of Texas at Austin, TX, USA
- affiliation (PhD): Eindhoven University of Technology, Eindhoven, The Netherlands
Other persons with the same name
- Shiwei Liu (aka: Shi-Wei Liu) — disambiguation page
- Shiwei Liu 0001
— Huazhong Agricultural University, College of Engineering, Wuhan, China
- Shiwei Liu 0002
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2020 – today
- 2024
- [c38]Ajay Jaiswal, Bodun Hu, Lu Yin, Yeonju Ro, Tianlong Chen, Shiwei Liu, Aditya Akella:
FFN-SkipLLM: A Hidden Gem for Autoregressive Decoding with Adaptive Feed Forward Skipping. EMNLP 2024: 16943-16956 - [c37]Abhinav Bandari, Lu Yin, Cheng-Yu Hsieh, Ajay Jaiswal, Tianlong Chen, Li Shen, Ranjay Krishna, Shiwei Liu:
Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning. EMNLP 2024: 18089-18099 - [c36]Yuxin Zhang, Lirui Zhao, Mingbao Lin, Yunyun Sun, Yiwu Yao, Xingjia Han, Jared Tanner, Shiwei Liu, Rongrong Ji:
Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs. ICLR 2024 - [c35]Gen Li, Lu Yin, Jie Ji, Wei Niu, Minghai Qin, Bin Ren, Linke Guo, Shiwei Liu, Xiaolong Ma:
NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization. ICLR 2024 - [c34]Enneng Yang, Zhenyi Wang, Li Shen, Shiwei Liu, Guibing Guo, Xingwei Wang, Dacheng Tao:
AdaMerging: Adaptive Model Merging for Multi-Task Learning. ICLR 2024 - [c33]Yuxin Zhang, Yuxuan Du, Gen Luo, Yunshan Zhong, Zhenyu Zhang, Shiwei Liu, Rongrong Ji:
CaM: Cache Merging for Memory-efficient LLMs Inference. ICML 2024 - [c32]Lu Yin, Ajay Kumar Jaiswal, Shiwei Liu, Souvik Kundu, Zhangyang Wang:
Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs "Difficult" Downstream Tasks in LLMs. ICML 2024 - [c31]Lu Yin, You Wu, Zhenyu Zhang, Cheng-Yu Hsieh, Yaqing Wang, Yiling Jia, Gen Li, Ajay Kumar Jaiswal, Mykola Pechenizkiy, Yi Liang, Michael Bendersky, Zhangyang Wang, Shiwei Liu:
Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. ICML 2024 - [c30]Jie Ji, Gen Li, Lu Yin, Minghai Qin, Geng Yuan, Linke Guo, Shiwei Liu, Xiaolong Ma:
Advancing Dynamic Sparse Training by Exploring Optimization Opportunities. ICML 2024 - [c29]Zhangheng Li, Shiwei Liu, Tianlong Chen, Ajay Kumar Jaiswal, Zhenyu Zhang, Dilin Wang, Raghuraman Krishnamoorthi, Shiyu Chang, Zhangyang Wang:
Sparse Cocktail: Every Sparse Pattern Every Sparse Ratio All At Once. ICML 2024 - [c28]Zhenyu Zhang, Shiwei Liu, Runjin Chen, Bhavya Kailkhura, Beidi Chen, Atlas Wang:
Q-Hitter: A Better Token Oracle for Efficient LLM Inference via Sparse-Quantized KV Cache. MLSys 2024 - [i47]Zhenyu Zhang, Runjin Chen, Shiwei Liu, Zhewei Yao, Olatunji Ruwase, Beidi Chen, Xiaoxia Wu, Zhangyang Wang:
Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding. CoRR abs/2403.04797 (2024) - [i46]Ajay Jaiswal, Bodun Hu, Lu Yin, Yeonju Ro, Shiwei Liu, Tianlong Chen, Aditya Akella:
FFN-SkipLLM: A Hidden Gem for Autoregressive Decoding with Adaptive Feed Forward Skipping. CoRR abs/2404.03865 (2024) - [i45]Pengxiang Li, Lu Yin, Xiaowei Gao, Shiwei Liu:
OwLore: Outlier-weighed Layerwise Sampled Low-Rank Projection for Memory-Efficient LLM Fine-tuning. CoRR abs/2405.18380 (2024) - [i44]Anke Tang, Li Shen, Yong Luo, Shiwei Liu, Han Hu, Bo Du:
Towards Efficient Pareto Set Approximation via Mixture of Experts Based Model Fusion. CoRR abs/2406.09770 (2024) - [i43]Adriana Fernandez-Lopez, Honglie Chen, Pingchuan Ma, Lu Yin, Qiao Xiao, Stavros Petridis, Shiwei Liu, Maja Pantic:
MSRS: Training Multimodal Speech Recognition Models from Scratch with Sparse Mask Optimization. CoRR abs/2406.17614 (2024) - [i42]Qiao Xiao, Pingchuan Ma, Adriana Fernandez-Lopez, Boqian Wu, Lu Yin, Stavros Petridis, Mykola Pechenizkiy, Maja Pantic, Decebal Constantin Mocanu, Shiwei Liu:
Dynamic Data Pruning for Automatic Speech Recognition. CoRR abs/2406.18373 (2024) - [i41]Arinbjorn Kolbeinsson, Kyle O'Brien, Tianjin Huang, Shanghua Gao, Shiwei Liu, Jonathan Richard Schwarz, Anurag Vaidya, Faisal Mahmood, Marinka Zitnik, Tianlong Chen, Thomas Hartvigsen:
Composable Interventions for Language Models. CoRR abs/2407.06483 (2024) - [i40]Zhenyu Zhang, Ajay Jaiswal, Lu Yin, Shiwei Liu, Jiawei Zhao, Yuandong Tian, Zhangyang Wang:
Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients. CoRR abs/2407.08296 (2024) - [i39]Ajay Jaiswal, Lu Yin, Zhenyu Zhang, Shiwei Liu, Jiawei Zhao, Yuandong Tian, Zhangyang Wang:
From GaLore to WeLore: How Low-Rank Weights Non-uniformly Emerge from Low-Rank Gradients. CoRR abs/2407.11239 (2024) - [i38]Tianjin Huang, Meng Fang, Li Shen, Fan Liu, Yulong Pei, Mykola Pechenizkiy, Shiwei Liu, Tianlong Chen:
(PASS) Visual Prompt Locates Good Structure Sparsity through a Recurrent HyperNetwork. CoRR abs/2407.17412 (2024) - [i37]Abhinav Bandari, Lu Yin, Cheng-Yu Hsieh, Ajay Kumar Jaiswal, Tianlong Chen, Li Shen, Ranjay Krishna, Shiwei Liu:
Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning. CoRR abs/2410.07461 (2024) - [i36]Adriana Fernandez-Lopez, Shiwei Liu, Lu Yin, Stavros Petridis, Maja Pantic:
Full-Rank No More: Low-Rank Weight Training for Modern Speech Recognition Models. CoRR abs/2410.07771 (2024) - 2023
- [j5]Shiwei Liu, Yuesong Tian, Tianlong Chen, Li Shen
Don't Be So Dense: Sparse-to-Sparse GAN Training Without Sacrificing Performance. Int. J. Comput. Vis. 131(10): 2635-2648 (2023) - [j4]Zahra Atashgahi, Xuhao Zhang, Neil Kichler, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu:
Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks. Trans. Mach. Learn. Res. 2023 (2023) - [c27]Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy:
Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost. AAAI 2023: 10945-10953 - [c26]Ruisi Cai, Xiaohan Chen, Shiwei Liu, Jayanth Srinivasa, Myungjin Lee, Ramana Kompella, Zhangyang Wang:
Many-Task Federated Learning: A New Problem Setting and A Simple Baseline. CVPR Workshops 2023: 5037-5045 - [c25]Enneng Yang
Data Augmented Flatness-aware Gradient Projection for Continual Learning. ICCV 2023: 5607-5616 - [c24]Tianlong Chen, Zhenyu Zhang, Ajay Kumar Jaiswal, Shiwei Liu, Zhangyang Wang:
Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers. ICLR 2023 - [c23]Duc N. M. Hoang, Shiwei Liu, Radu Marculescu, Zhangyang Wang:
Revisiting Pruning at Initialization Through the Lens of Ramanujan Graph. ICLR 2023 - [c22]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Tommi Kärkkäinen, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang:
More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity. ICLR 2023 - [c21]Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Kumar Jaiswal, Zhangyang Wang:
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! ICLR 2023 - [c20]Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu:
Are Large Kernels Better Teachers than Transformers for ConvNets? ICML 2023: 14023-14038 - [c19]Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang:
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication. ICML 2023: 14679-14690 - [c18]Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang:
Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models. ICML 2023: 14691-14701 - [c17]Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu:
Dynamic Sparsity Is Channel-Level Sparsity Learner. NeurIPS 2023 - [c16]Duc Hoang, Souvik Kundu, Shiwei Liu, Zhangyang Wang:
Don't just prune by magnitude! Your mask topology is a secret weapon. NeurIPS 2023 - [c15]Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Zhangyang Wang:
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter. NeurIPS 2023 - [c14]Hoang Pham, The-Anh Ta, Shiwei Liu, Lichuan Xiang, Dung Le, Hongkai Wen, Long Tran-Thanh:
Towards Data-Agnostic Pruning At Initialization: What Makes a Good Sparse Mask? NeurIPS 2023 - [c13]Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy:
Enhancing Adversarial Training via Reweighting Optimization Trajectory. ECML/PKDD (1) 2023: 113-130 - [c12]Jiaxu Zhao, Lu Yin, Shiwei Liu, Meng Fang, Mykola Pechenizkiy:
REST: Enhancing Group Robustness in DNNs Through Reweighted Sparse Training. ECML/PKDD (2) 2023: 313-329 - [i35]Shiwei Liu, Zhangyang Wang:
Ten Lessons We Have Learned in the New "Sparseland": A Short Handbook for Sparse Neural Network Researchers. CoRR abs/2302.02596 (2023) - [i34]Tianlong Chen, Zhenyu Zhang, Ajay Jaiswal, Shiwei Liu, Zhangyang Wang:
Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers. CoRR abs/2303.01610 (2023) - [i33]Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Jaiswal, Zhangyang Wang:
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! CoRR abs/2303.02141 (2023) - [i32]Zahra Atashgahi, Xuhao Zhang, Neil Kichler
Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks. CoRR abs/2303.07200 (2023) - [i31]Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu:
Are Large Kernels Better Teachers than Transformers for ConvNets? CoRR abs/2305.19412 (2023) - [i30]Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu:
Dynamic Sparsity Is Channel-Level Sparsity Learner. CoRR abs/2305.19454 (2023) - [i29]Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Zhangyang Wang:
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter. CoRR abs/2306.03805 (2023) - [i28]Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang:
Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models. CoRR abs/2306.10460 (2023) - [i27]Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang:
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication. CoRR abs/2306.10466 (2023) - [i26]Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy:
Enhancing Adversarial Training via Reweighting Optimization Trajectory. CoRR abs/2306.14275 (2023) - [i25]Lu Yin, Shiwei Liu, Ajay Jaiswal, Souvik Kundu, Zhangyang Wang:
Junk DNA Hypothesis: A Task-Centric Angle of LLM Pre-trained Weights through Sparsity. CoRR abs/2310.02277 (2023) - [i24]Enneng Yang, Zhenyi Wang, Li Shen, Shiwei Liu, Guibing Guo, Xingwei Wang, Dacheng Tao:
AdaMerging: Adaptive Model Merging for Multi-Task Learning. CoRR abs/2310.02575 (2023) - [i23]Lu Yin, You Wu, Zhenyu Zhang, Cheng-Yu Hsieh, Yaqing Wang, Yiling Jia, Mykola Pechenizkiy, Yi Liang, Zhangyang Wang, Shiwei Liu:
Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. CoRR abs/2310.05175 (2023) - [i22]Yuxin Zhang, Lirui Zhao, Mingbao Lin, Yunyun Sun, Yiwu Yao, Xingjia Han, Jared Tanner, Shiwei Liu, Rongrong Ji:
Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs. CoRR abs/2310.08915 (2023) - [i21]Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen:
Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective. CoRR abs/2312.01397 (2023) - [i20]Jiaxu Zhao, Lu Yin, Shiwei Liu, Meng Fang, Mykola Pechenizkiy:
REST: Enhancing Group Robustness in DNNs through Reweighted Sparse Training. CoRR abs/2312.03044 (2023) - [i19]Boqian Wu, Qiao Xiao, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Decebal Constantin Mocanu, Maurice van Keulen, Elena Mocanu
E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation. CoRR abs/2312.04727 (2023) - [i18]Tianjin Huang, Tianlong Chen, Zhangyang Wang, Shiwei Liu:
The Counterattack of CNNs in Self-Supervised Learning: Larger Kernel Size might be All You Need. CoRR abs/2312.05695 (2023) - 2022
- [j3]Zahra Atashgahi
A brain-inspired algorithm for training highly sparse neural networks. Mach. Learn. 111(12): 4411-4452 (2022) - [c11]Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu:
Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity. ICLR 2022 - [c10]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy:
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training. ICLR 2022 - [c9]Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu:
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. LoG 2022: 8 - [c8]Qiao Xiao, Boqian Wu, Yu Zhang, Shiwei Liu, Mykola Pechenizkiy, Elena Mocanu, Decebal Constantin Mocanu:
Dynamic Sparse Network for Time Series Classification: Learning What to "See". NeurIPS 2022 - [i17]Tiansheng Huang, Shiwei Liu, Li Shen, Fengxiang He, Weiwei Lin, Dacheng Tao:
Achieving Personalized Federated Learning with Sparse Local Models. CoRR abs/2201.11380 (2022) - [i16]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy:
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training. CoRR abs/2202.02643 (2022) - [i15]Shiwei Liu, Yuesong Tian, Tianlong Chen, Li Shen:
Don't Be So Dense: Sparse-to-Sparse GAN Training Without Sacrificing Performance. CoRR abs/2203.02770 (2022) - [i14]Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy, Decebal Constantin Mocanu, Shiwei Liu:
Superposing Many Tickets into One: A Performance Booster for Sparse Neural Network Training. CoRR abs/2205.15322 (2022) - [i13]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang:
More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity. CoRR abs/2207.03620 (2022) - [i12]Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy:
Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost. CoRR abs/2208.10842 (2022) - [i11]Tianjin Huang
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. CoRR abs/2211.15335 (2022) - [i10]Qiao Xiao, Boqian Wu, Yu Zhang, Shiwei Liu, Mykola Pechenizkiy, Elena Mocanu
Dynamic Sparse Network for Time Series Classification: Learning What to "see". CoRR abs/2212.09840 (2022) - 2021
- [j2]Shiwei Liu, Decebal Constantin Mocanu
Sparse evolutionary deep learning with over one million artificial neurons on commodity hardware. Neural Comput. Appl. 33(7): 2589-2604 (2021) - [j1]Shiwei Liu
Efficient and effective training of sparse recurrent neural networks. Neural Comput. Appl. 33(15): 9625-9636 (2021) - [c7]Lu Yin, Vlado Menkovski, Shiwei Liu, Mykola Pechenizkiy:
Hierarchical Semantic Segmentation using Psychometric Learning. ACML 2021: 798-813 - [c6]Shiwei Liu, Decebal Constantin Mocanu, Yulong Pei, Mykola Pechenizkiy:
Selfish Sparse RNN Training. ICML 2021: 6893-6904 - [c5]Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy:
Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training. ICML 2021: 6989-7000 - [c4]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu:
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. NeurIPS 2021: 9908-9922 - [i9]Shiwei Liu, Decebal Constantin Mocanu, Yulong Pei, Mykola Pechenizkiy:
Selfish Sparse RNN Training. CoRR abs/2101.09048 (2021) - [i8]Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy:
Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training. CoRR abs/2102.02887 (2021) - [i7]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu:
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. CoRR abs/2106.10404 (2021) - [i6]Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu
FreeTickets: Accurate, Robust and Efficient Deep Ensemble by Training with Dynamic Sparsity. CoRR abs/2106.14568 (2021) - [i5]Lu Yin, Vlado Menkovski, Shiwei Liu, Mykola Pechenizkiy:
Hierarchical Semantic Segmentation using Psychometric Learning. CoRR abs/2107.03212 (2021) - 2020
- [c3]Fulong Yan, Shiwei Liu, Nicola Calabretta:
Network Performance Optimization with Real Time Traffic Prediction in Data Center Network. ECOC 2020: 1-4 - [c2]Shiwei Liu:
Learning Sparse Neural Networks for Better Generalization. IJCAI 2020: 5190-5191 - [c1]Shiwei Liu, Tim van der Lee, Anil Yaman
Topological Insights into Sparse Neural Networks. ECML/PKDD (3) 2020: 279-294 - [i4]Shiwei Liu, Tim van der Lee, Anil Yaman, Zahra Atashgahi, Davide Ferraro, Ghada Sokar
Topological Insights in Sparse Neural Networks. CoRR abs/2006.14085 (2020)
2010 – 2019
- 2019
- [i3]Shiwei Liu, Decebal Constantin Mocanu, Amarsagar Reddy Ramapuram Matavalam, Yulong Pei, Mykola Pechenizkiy:
Sparse evolutionary Deep Learning with over one million artificial neurons on commodity hardware. CoRR abs/1901.09181 (2019) - [i2]Shiwei Liu, Decebal Constantin Mocanu, Mykola Pechenizkiy:
Intrinsically Sparse Long Short-Term Memory Networks. CoRR abs/1901.09208 (2019) - [i1]Shiwei Liu, Decebal Constantin Mocanu, Mykola Pechenizkiy:
On improving deep learning generalization with adaptive sparse connectivity. CoRR abs/1906.11626 (2019)
Coauthor Index
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