| Spike-thrift: Towards energy-efficient deep spiking neural networks by limiting spiking activity via attention-guided compression S Kundu, G Datta, M Pedram, PA Beerel IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2021 …, 2021 | 111 | 2021 |
| HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training With Crafted Input Noise S Kundu, M Pedram, PA Beerel IEEE/CVF International Conference on Computer Vision (ICCV 2021), 5209-5218, 2021 | 66 | 2021 |
| DNR: A Tunable Robust Pruning Framework Through Dynamic Network Rewiring of DNNs S Kundu, M Nazemi, PA Beerel, M Pedram Proceedings of the 26th ASP-DAC 2021, 344-350, 2021 | 65 | 2021 |
| Pre-Defined Sparsity for Low-Complexity Convolutional Neural Networks S Kundu, M Nazemi, M Pedram, KM Chugg, PA Beerel IEEE Transactions on Computers 2020 69 (7), 1045-1058, 2020 | 49 | 2020 |
| Training Energy-Efficient Deep Spiking Neural Networks with Single-Spike Hybrid Input Encoding G Datta, S Kundu, PA Beerel IJCNN 2021, 2021 | 37 | 2021 |
| P2M: A Processing-in-Pixel-in-Memory Paradigm for Resource-Constrained TinyML Applications S Kundu, G Datta, Z Yin, RT Lakkireddy, PA Beerel, A Jacob, ARE Jaiswal Nature Scientific Reports 2022, 2022 | 32* | 2022 |
| Learning to Linearize Deep Neural Networks for Secure and Efficient Private Inference S Kundu, S Lu, Y Zhang, J Liu, PA Beerel International Conference on Learning Representation (ICLR) 2023., 2023 | 31 | 2023 |
| ACE-SNN: Algorithm-Hardware Co-Design of Energy-efficient & Low-Latency Deep Spiking Neural Networks for 3D Image Recognition G Datta, S Kundu, A Jaiswal, PA Beerel Frontiers in Neuroscience, 2022 | 29* | 2022 |
| Analyzing the Confidentiality of Undistillable Teachers in Knowledge Distillation S Kundu, Q Sun, Y Fu, M Pedram, P Beerel Advances in Neural Information Processing Systems (NeurIPS 2021) 34, 2021 | 26 | 2021 |
| AttentionLite: Towards Efficient Self-Attention Models for Vision S Kundu, S Sundaresan ICASSP 2021, 2021 | 26 | 2021 |
| Pipeedge: Pipeline parallelism for large-scale model inference on heterogeneous edge devices Y Hu, C Imes, X Zhao, S Kundu, PA Beerel, SP Crago, JP Walters 2022 25th Euromicro Conference on Digital System Design (DSD), 298-307, 2022 | 25* | 2022 |
| Revisiting Sparsity Hunting in Federated Learning: Why does Sparsity Consensus Matter? S Kundu*, S Babakniya*, S Prakash, Y Niu, S Avestimehr Transactions on Machine Learning Research (TMLR), 2023 | 20* | 2023 |
| A highly parallel FPGA implementation of sparse neural network training S Dey, D Chen, Z Li, S Kundu, KW Huang, KM Chugg, PA Beerel 2018 International Conference on ReConFigurable Computing and FPGAs …, 2018 | 20 | 2018 |
| Towards Low-Latency Energy-Efficient Deep SNNs via Attention-Guided Compression S Kundu, G Datta, M Pedram, PA Beerel 2nd Sparse Neural Networks Workshop (co-located with ICML 2022), 2021 | 19 | 2021 |
| pSConv: A Pre-defined S parse Kernel Based Convolution for Deep CNNs S Kundu, S Prakash, H Akrami, PA Beerel, KM Chugg 2019 57th Annual Allerton Conference on Communication, Control, and …, 2019 | 17* | 2019 |
| Making Models Shallow Again: Jointly Learning to Reduce Non-Linearity and Depth for Latency-Efficient Private Inference S Kundu, Y Zhang, D Chen, P Beerel CVPR 2023 Efficient Computer Vision (ORAL), 2023 | 16 | 2023 |
| BMPQ: Bit-Gradient Sensitivity Driven Mixed-Precision Quantization of DNNs from Scratch S Kundu, S Wang, Q Sun, PA Beerel, M Pedram Design Automation and Test in Europe (DATE) 2022, 2021 | 16 | 2021 |
| ViTA: A Vision Transformer Inference Accelerator for Edge Applications S Nag, G Datta, S Kundu, N Chandrachoodan, PA Beerel ISCAS 2023, 2023 | 15 | 2023 |
| Toward Adversary-aware Non-iterative Model Pruning through Dynamic Network Rewiring of DNNs S Kundu, Y Fu, B Ye, PA Beerel, M Pedram ACM Transactions on Embedded Computing Systems 21 (5), 1-24, 2022 | 14 | 2022 |
| P2M-DeTrack: Processing-in-Pixel-in-Memory for Energy-efficient and Real-Time Multi-Object Detection and Tracking S Kundu, G Datta, Z Yin, J Mathai, Z Liu, Z Wang, M Tian, S Lu, ... VLSI-SoC 2022, 2022 | 13* | 2022 |
Peter BeerelProfessor of Electrical and Computer Engineering, USC在 usc.edu 的电子邮件经过验证
