278 results on '"Nicholas D. Lane"'
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2. L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning.
3. Can Fair Federated Learning Reduce the need for Personalisation?
4. Gradient-less Federated Gradient Boosting Tree with Learnable Learning Rates.
5. A Federated Learning Benchmark for Drug-Target Interaction.
6. Sparse-DySta: Sparsity-Aware Dynamic and Static Scheduling for Sparse Multi-DNN Workloads.
7. FedVal: Different good or different bad in federated learning.
8. Decentralized Training of 3D Lane Detection with Automatic Labeling Using HD Maps.
9. Learn2Agree: Fitting with Multiple Annotators Without Objective Ground Truth.
10. Zero-Cost Operation Scoring in Differentiable Architecture Search.
11. Deep learning on microcontrollers: a study on deployment costs and challenges.
12. Federated Self-supervised Speech Representations: Are We There Yet?
13. Adaptable Butterfly Accelerator for Attention-based NNs via Hardware and Algorithm Co-design.
14. Protea: client profiling within federated systems using flower.
15. End-to-End Speech Recognition from Federated Acoustic Models.
16. Match to Win: Analysing Sequences Lengths for Efficient Self-Supervised Learning in Speech and Audio.
17. Federated Self-supervised Learning for Video Understanding.
18. Multi-Exit Semantic Segmentation Networks.
19. FedL2P: Federated Learning to Personalize.
20. μNAS: Constrained Neural Architecture Search for Microcontrollers.
21. Temporal Kernel Consistency for Blind Video Super-Resolution.
22. FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout.
23. Secure aggregation for federated learning in flower.
24. unzipFPGA: Enhancing FPGA-based CNN Engines with On-the-Fly Weights Generation.
25. Distilling Knowledge from Ensembles of Acoustic Models for Joint CTC-Attention End-to-End Speech Recognition.
26. Smart at what cost?: characterising mobile deep neural networks in the wild.
27. It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation.
28. Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions.
29. Are Mobile DNN Accelerators Accelerating DNNs?
30. Neural Enhancement in Content Delivery Systems: The State-of-the-Art and Future Directions.
31. EMOPAIN Challenge 2020: Multimodal Pain Evaluation from Facial and Bodily Expressions.
32. Unsupervised Domain Adaptation Under Label Space Mismatch for Speech Classification.
33. Iterative Compression of End-to-End ASR Model Using AutoML.
34. Bunched LPCNet: Vocoder for Low-Cost Neural Text-To-Speech Systems.
35. Quaternion Neural Networks for Multi-Channel Distant Speech Recognition.
36. FusionRNN: Shared Neural Parameters for Multi-Channel Distant Speech Recognition.
37. HAPI: Hardware-Aware Progressive Inference.
38. SPINN: synergistic progressive inference of neural networks over device and cloud.
39. The Final Frontier: Deep Learning in Space.
40. Are Accelerometers for Activity Recognition a Dead-end?
41. Libri-Adapt: a New Speech Dataset for Unsupervised Domain Adaptation.
42. Journey Towards Tiny Perceptual Super-Resolution.
43. Best of Both Worlds: AutoML Codesign of a CNN and its Hardware Accelerator.
44. BLOX: Macro Neural Architecture Search Benchmark and Algorithms.
45. Adaptable mobile vision systems through multi-exit neural networks.
46. ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning.
47. Recurrent network based automatic detection of chronic pain protective behavior using MoCap and sEMG data.
48. Unsupervised domain adaptation for robust sensory systems.
49. MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors.
50. Learning Temporal and Bodily Attention in Protective Movement Behavior Detection.
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