PowerPoint 簡報

1. Structured Support Vector Machine
2. 公告
3. 公告
4. Structured Learning
5. Unified Framework
6. Three Problems
7. Example Task: Object Detection
8. Problem 1: Evaluation
9. Problem 2: Inference
10. Problem 2: Inference
11. Problem 3: Training
12. Outline
13. Outline
14. Assumption: Separable
15. Structured Perceptron
16. Warning of Math
17. Proof of Termination
18. Proof of Termination
19. Proof of Termination
20. Proof of Termination
21. Proof of Termination
22. End of Warning
23. How to make training fast?
24. Outline
25. Non-separable Case
26. Defining Cost Function
27. (Stochastic) Gradient Descent
28. When w is different, the y can be different.
29. (Stochastic) Gradient Descent
30. Outline
31. Outline
32. Based on what we have considered …...
33. Considering the incorrect ones
34. Defining Error Function
35. Another Cost Function
36. Gradient Descent
37. Another Viewpoint
38. Another Viewpoint
39. More Cost Functions
40. Outline
41. Regularization
42. Regularization
43. Outline
44. Structured SVM
45. Structured SVM
46. Structured SVM
47. Structured SVM
48. Structured SVM
49. margin
50. Structured SVM
51. margin
52. Structured SVM - Intuition
53. Training data:
54. Structured SVM
55. Outline
56. Slide 50
57. Cutting Plane Algorithm
58. Cutting Plane Algorithm
59. Cutting Plane Algorithm
60. Cutting Plane Algorithm
61. Cutting Plane Algorithm
62. Cutting Plane Algorithm
63. Find the most violated one
64. Cutting Plane Algorithm
65. Cutting Plane Algorithm
66. Training data:
67. Training data:
68. Training data:
69. Training data:
70. Training data:
71. Training data:
72. Training data:
73. Concluding Remarks
74. Multi-class SVM
75. Multi-class SVM
76. Multi-class SVM
77. Binary SVM
78. Concluding Remarks
79. Beyond Structured SVM
80. Beyond Structured SVM
81. Beyond Structured SVM
82. Concluding Remarks

1. Structured Support Vector Machine
2. 公告
3. 公告
4. Structured Learning
5. Unified Framework
6. Three Problems
7. Example Task: Object Detection
8. Problem 1: Evaluation
9. Problem 2: Inference
10. Problem 2: Inference
11. Problem 3: Training
12. Outline
13. Outline
14. Assumption: Separable
15. Structured Perceptron
16. Warning of Math
17. Proof of Termination
18. Proof of Termination
19. Proof of Termination
20. Proof of Termination
21. Proof of Termination
22. End of Warning
23. How to make training fast?
24. Outline
25. Non-separable Case
26. Defining Cost Function
27. (Stochastic) Gradient Descent
28. When w is different, the y can be different.
29. (Stochastic) Gradient Descent
30. Outline
31. Outline
32. Based on what we have considered …...
33. Considering the incorrect ones
34. Defining Error Function
35. Another Cost Function
36. Gradient Descent
37. Another Viewpoint
38. Another Viewpoint
39. More Cost Functions
40. Outline
41. Regularization
42. Regularization
43. Outline
44. Structured SVM
45. Structured SVM
46. Structured SVM
47. Structured SVM
48. Structured SVM
49. margin
50. Structured SVM
51. margin
52. Structured SVM - Intuition
53. Training data:
54. Structured SVM
55. Outline
56. Slide 50
57. Cutting Plane Algorithm
58. Cutting Plane Algorithm
59. Cutting Plane Algorithm
60. Cutting Plane Algorithm
61. Cutting Plane Algorithm
62. Cutting Plane Algorithm
63. Find the most violated one
64. Cutting Plane Algorithm
65. Cutting Plane Algorithm
66. Training data:
67. Training data:
68. Training data:
69. Training data:
70. Training data:
71. Training data:
72. Training data:
73. Concluding Remarks
74. Multi-class SVM
75. Multi-class SVM
76. Multi-class SVM
77. Binary SVM
78. Concluding Remarks
79. Beyond Structured SVM
80. Beyond Structured SVM
81. Beyond Structured SVM
82. Concluding Remarks

1/82

Volume

速度 :
畫質 :
1024 x 768

00:00/2:11:44

00:00/00:46