Dr. Tan LI, 李檀

Computer Science

1. Distributed Learning 100%
2. Deep Reinforcement Learning 100%
3. Differential Privacy 91%
4. Federated machine learning 83%
5. Energy Consumption 80%
6. Project Management 80%
7. Stochastic Gradient Descent 75%
8. Communication Cost 66%
9. multi agent 66%
10. Electronic Learning 66%
11. Edge Server 50%
12. Privacy Protection 50%
13. Biometrics 50%
14. Wearable Device 50%
15. Network Traffic 50%
16. User Authentication 50%
17. Privacy Preserving 50%
18. Internet of Vehicles 50%
19. Edge Computing 50%
20. Unsupervised Domain Adaptation 50%
21. Multiobjective 50%
22. Traffic Classification 50%
23. Learning Algorithm 50%
24. Resource Allocation 50%
25. Non-Orthogonal Multiple Access 50%
26. Sparsification 50%
27. Learning Performance 41%
28. State Space 35%
29. Requirements Management 35%
30. Performance Gain 35%
31. Compression Problem 33%
32. Budget Constraint 33%
33. Edge Caching 33%
34. Data Privacy 33%
35. Objective Optimization 29%
36. Learning System 26%
37. Gradient Method 25%
38. Smart Grid 25%
39. Task Offloading 25%
40. Problem Management 25%
41. Deep Neural Network 25%
42. Distributed Machine Learning 25%
43. Experimental Result 25%
44. Implementation Complexity 25%
45. task-scheduling 25%
46. Learning Framework 25%
47. Data Distribution 25%
48. Biggest Challenge 25%
49. Interdependence 25%
50. Electricity Consumption 20%