47 results on '"Deliang Fan"'
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2. LP-3DGS: Learning to Prune 3D Gaussian Splatting.
3. Efficient Self-supervised Continual Learning with Progressive Task-correlated Layer Freezing.
4. MF-NeRF: Memory Efficient NeRF with Mixed-Feature Hash Table.
5. Model Extraction Attacks on Split Federated Learning.
6. TRGP: Trust Region Gradient Projection for Continual Learning.
7. ResSFL: A Resistance Transfer Framework for Defending Model Inversion Attack in Split Federated Learning.
8. Beyond Not-Forgetting: Continual Learning with Backward Knowledge Transfer.
9. Gradient-based Novelty Detection Boosted by Self-supervised Binary Classification.
10. NeurObfuscator: A Full-stack Obfuscation Tool to Mitigate Neural Architecture Stealing.
11. DeepSteal: Advanced Model Extractions Leveraging Efficient Weight Stealing in Memories.
12. RA-BNN: Constructing Robust & Accurate Binary Neural Network to Simultaneously Defend Adversarial Bit-Flip Attack and Improve Accuracy.
13. RADAR: Run-time Adversarial Weight Attack Detection and Accuracy Recovery.
14. GROWN: GRow Only When Necessary for Continual Learning.
15. DA2: Deep Attention Adapter for Memory-EfficientOn-Device Multi-Domain Learning.
16. MetaGater: Fast Learning of Conditional Channel Gated Networks via Federated Meta-Learning.
17. PANDA: Processing-in-MRAM Accelerated De Bruijn Graph based DNA Assembly.
18. Deep-Dup: An Adversarial Weight Duplication Attack Framework to Crush Deep Neural Network in Multi-Tenant FPGA.
19. MERAM: Non-Volatile Cache Memory Based on Magneto-Electric FETs.
20. T-BFA: Targeted Bit-Flip Adversarial Weight Attack.
21. KSM: Fast Multiple Task Adaption via Kernel-wise Soft Mask Learning.
22. DeepHammer: Depleting the Intelligence of Deep Neural Networks through Targeted Chain of Bit Flips.
23. A Progressive Sub-Network Searching Framework for Dynamic Inference.
24. Representable Matrices: Enabling High Accuracy Analog Computation for Inference of DNNs using Memristors.
25. Defending Against Adversarial Attacks Using Random Forests.
26. Non-structured DNN Weight Pruning Considered Harmful.
27. Processing-In-Memory Acceleration of Convolutional Neural Networks for Energy-Efficiency, and Power-Intermittency Resilience.
28. TBT: Targeted Neural Network Attack with Bit Trojan.
29. Bit-Flip Attack: Crushing Neural Network withProgressive Bit Search.
30. Robust Sparse Regularization: Simultaneously Optimizing Neural Network Robustness and Compactness.
31. Accelerating Bulk Bit-Wise X(N)OR Operation in Processing-in-DRAM Platform.
32. Optimize Deep Convolutional Neural Network with Ternarized Weights and High Accuracy.
33. Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness against Adversarial Attack.
34. Blind Pre-Processing: A Robust Defense Method Against Adversarial Examples.
35. A Semi-Supervised Two-Stage Approach to Learning from Noisy Labels.
36. Simultaneously Optimizing Weight and Quantizer of Ternary Neural Network using Truncated Gaussian Approximation.
37. Defend Deep Neural Networks Against Adversarial Examples via Fixed andDynamic Quantized Activation Functions.
38. Developing All-Skyrmion Spiking Neural Network.
39. Current Induced Dynamics of Multiple Skyrmions with Domain Wall Pair and Skyrmion-based Majority Gate Design.
40. Hierarchical Temporal Memory Based on Spin-Neurons and Resistive Memory for Energy-Efficient Brain-Inspired Computing.
41. Design and Synthesis of Ultra Low Energy Spin-Memristor Threshold Logic.
42. STT-SNN: A Spin-Transfer-Torque Based Soft-Limiting Non-Linear Neuron for Low-Power Artificial Neural Networks.
43. Exploring Boolean and Non-Boolean Computing Applications of Spin Torque Devices.
44. Ultra-low Energy, High-Performance Dynamic Resistive Threshold Logic.
45. Ultra Low Power Associative Computing with Spin Neurons and Resistive Crossbar Memory
46. Ultra-low Energy, High Performance and Programmable Magnetic Threshold Logic.
47. Spin Neurons: A Possible Path to Energy-Efficient Neuromorphic Computers.
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