Канал: Constantine Caramanis

Theorem of Alternatives from Separation

Theorem of Alternatives from Separation

Separating Hyperplanes

Separating Hyperplanes

11.7 Lower Bounding Extension Complexity, Part V

11.7 Lower Bounding Extension Complexity, Part V

11.1 Extended Formulations, Part I

11.1 Extended Formulations, Part I

11.6 Lower Bounding Extension Complexity, Part IV

11.6 Lower Bounding Extension Complexity, Part IV

11.5 Lower Bounding Extension Complexity, Part III

11.5 Lower Bounding Extension Complexity, Part III

11.4 Lower Bounding Extension Complexity, Part II

11.4 Lower Bounding Extension Complexity, Part II

11.2 Extended Formulations, Part II

11.2 Extended Formulations, Part II

11.3 Lower Bounding Extension Complexity, Part I

11.3 Lower Bounding Extension Complexity, Part I

10.7 Continuous Greedy, Part II

10.7 Continuous Greedy, Part II

10.6 Continuous Greedy, Part I

10.6 Continuous Greedy, Part I

10.5 Continuous Extensions, Part II

10.5 Continuous Extensions, Part II

10.4 Continuous Extensions, Part I

10.4 Continuous Extensions, Part I

10.3 Submodular Functions, Part III

10.3 Submodular Functions, Part III

10.2 Submodular Functions, Part II

10.2 Submodular Functions, Part II

10.1 Submodular Functions, Part I

10.1 Submodular Functions, Part I

9.13 Matroid Intersection, Part VI

9.13 Matroid Intersection, Part VI

9.12 Matroid Intersection, Part V

9.12 Matroid Intersection, Part V

9.11 Matroid Intersection, Part IV

9.11 Matroid Intersection, Part IV

5.7 Mirror Descent Part 3

5.7 Mirror Descent Part 3

Finishing up Newton's Method

Finishing up Newton's Method

5.4 ISTA and FISTA

5.4 ISTA and FISTA

7.2 Newton's Method and Affine Transformations

7.2 Newton's Method and Affine Transformations

1.2 What these Lectures do and do not cover

1.2 What these Lectures do and do not cover

3.4 Convergence Rates

3.4 Convergence Rates

9.3 Interior Point Methods - Part III

9.3 Interior Point Methods - Part III

1.1 Introduction to Optimization and to Me

1.1 Introduction to Optimization and to Me

3.1 Intro to Gradient and Subgradient Descent

3.1 Intro to Gradient and Subgradient Descent

5.1 Proximal and Projected Gradient Descent

5.1 Proximal and Projected Gradient Descent

3.3 Properties of Smooth and Strongly Convex Functions

3.3 Properties of Smooth and Strongly Convex Functions

5.9 Mirror Descent Part 4b

5.9 Mirror Descent Part 4b

5.8 Mirror Descent Part 4a

5.8 Mirror Descent Part 4a

8.1 Quasi Newton Methods Part I

8.1 Quasi Newton Methods Part I

6.3 SGD Part 3

6.3 SGD Part 3

5.2 Proximal Gradient -- Basic Properties

5.2 Proximal Gradient -- Basic Properties

5.5 Mirror Descent Part 1

5.5 Mirror Descent Part 1

1.3 Some First Examples

1.3 Some First Examples

9.1 Interior Point Methods - Part I

9.1 Interior Point Methods - Part I

6.4 SGD and SVRG

6.4 SGD and SVRG

5.11 Mirror Descent Part 6

5.11 Mirror Descent Part 6

4.1 Oracle Lower Bounds

4.1 Oracle Lower Bounds

8.2 Quasi Newton and BFGS

8.2 Quasi Newton and BFGS

2.5 Optimality Conditions for Convex Optimization

2.5 Optimality Conditions for Convex Optimization

5.6 Mirror Descent Part 2

5.6 Mirror Descent Part 2

9.2 Interior Point Methods - Part II

9.2 Interior Point Methods - Part II

5.3 Prox Gradient -- Rates of Convergence

5.3 Prox Gradient -- Rates of Convergence

3.2 Smooth and Strongly Convex Functions

3.2 Smooth and Strongly Convex Functions

2.6 Optimality Conditions and Projection

2.6 Optimality Conditions and Projection

7.4 Newton's Method -- Proof

7.4 Newton's Method -- Proof

1.4. Basics of linear algebra and calculus we need

1.4. Basics of linear algebra and calculus we need

6.1 Stochastic Gradient Descent - Intro

6.1 Stochastic Gradient Descent - Intro

2.4 Equivalence of Convex Function Definitions

2.4 Equivalence of Convex Function Definitions

6.2 SGD Part 2

6.2 SGD Part 2

4.2 Accelerated Gradient Descent

4.2 Accelerated Gradient Descent

2.3 Convex Functions

2.3 Convex Functions

5.12 Frank Wolfe

5.12 Frank Wolfe

7.3 Newton's Method -- Convergence Result

7.3 Newton's Method -- Convergence Result

6.5 SGD Part 5

6.5 SGD Part 5

7.1 Newton's Method - A First View

7.1 Newton's Method - A First View

2.2 Convex Sets -- Examples

2.2 Convex Sets -- Examples

2.1 Convex Sets: Definitions

2.1 Convex Sets: Definitions

5.10 Mirror Descent Part 5

5.10 Mirror Descent Part 5

10.1 Fenchel Dual Part I

10.1 Fenchel Dual Part I

10.2 Fenchel Dual Part II

10.2 Fenchel Dual Part II

9.4 Interior Point Methods - Part IV

9.4 Interior Point Methods - Part IV

11.6 Some Examples

11.6 Some Examples

12.1 Monotone Operators

12.1 Monotone Operators

12.4 DR Examples Part II

12.4 DR Examples Part II

11.2 Proximal Point and Augmented Lagrangian

11.2 Proximal Point and Augmented Lagrangian

11.1 Dual Decomposition

11.1 Dual Decomposition

12.3 DR Examples Part I

12.3 DR Examples Part I

1.1 Introduction

1.1 Introduction

12.5 ADMM -- DR in the Dual

12.5 ADMM -- DR in the Dual

10.3 Fenchel Dual Part IIΙ

10.3 Fenchel Dual Part IIΙ

10.4 Fenchel Dual Part IV

10.4 Fenchel Dual Part IV

11.3 Interpretations of PPA and ALM

11.3 Interpretations of PPA and ALM

12.2 Operator Splitting -- Douglas Rachford

12.2 Operator Splitting -- Douglas Rachford

11.4 Convergence of Prox Point Algorithm

11.4 Convergence of Prox Point Algorithm

11.5 Proximal Gradient in the Dual

11.5 Proximal Gradient in the Dual

2.4 The Simplex Method, Part III

2.4 The Simplex Method, Part III

5.2 Ellipsoid Algorithm, Part II

5.2 Ellipsoid Algorithm, Part II

3.4 The Primal Dual Framework, Part I

3.4 The Primal Dual Framework, Part I

5.1 Ellipsoid Algorithm, Part I

5.1 Ellipsoid Algorithm, Part I

3.1 LP Duality, Part I

3.1 LP Duality, Part I

7.1 Totally Unimodular Matrices, Part I

7.1 Totally Unimodular Matrices, Part I

3.5 The Primal Dual Framework, Part II

3.5 The Primal Dual Framework, Part II

6.1 Bipartite Matching, Part I

6.1 Bipartite Matching, Part I

2.3 The Simplex Method, Part II

2.3 The Simplex Method, Part II

4.4 Ford Fulkerson, Part I

4.4 Ford Fulkerson, Part I

4.5 Ford Fulkerson, Part II

4.5 Ford Fulkerson, Part II

3.3 LP Duality, Part III

3.3 LP Duality, Part III

4.2 Primal Dual Applied to Shortest Path

4.2 Primal Dual Applied to Shortest Path

2.2 The Simplex Method, Part I

2.2 The Simplex Method, Part I

5.4 Strong and Weak Oracles, Part I

5.4 Strong and Weak Oracles, Part I

3.2 LP Duality, Part II

3.2 LP Duality, Part II

5.6 Rational Polyhedra

5.6 Rational Polyhedra

4.1 Some Network Flow Problems

4.1 Some Network Flow Problems

4.6 r-Arborescences

4.6 r-Arborescences

2.1 Polytopes and Extreme Points

2.1 Polytopes and Extreme Points

7.2 Totally Unimodular Matrices, Part II

7.2 Totally Unimodular Matrices, Part II

5.5 Strong and Weak Oracles, Part II

5.5 Strong and Weak Oracles, Part II

6.2 Bipartite Matching, Part II

6.2 Bipartite Matching, Part II

4.3 Primal Dual Applied to Max Flow

4.3 Primal Dual Applied to Max Flow

5.3 Ellipsoid Algorithm, Part III

5.3 Ellipsoid Algorithm, Part III

9.10 Matroid Intersection, Part III

9.10 Matroid Intersection, Part III

7.8 r-Arborescences and TDI, Part II

7.8 r-Arborescences and TDI, Part II

9.9 Matroid Intersection, Part II

9.9 Matroid Intersection, Part II

9.8 Matroid Intersection, Part I

9.8 Matroid Intersection, Part I

9.2 Matroids, Part II

9.2 Matroids, Part II

9.5 Matroids, Part V

9.5 Matroids, Part V

8.6 The Matching Polytope, Part I

8.6 The Matching Polytope, Part I

8.5 Non Bipartite Matching, Part V

8.5 Non Bipartite Matching, Part V

8.9 Max Weight Matching, Part I

8.9 Max Weight Matching, Part I

9.1 Matroids, Part I

9.1 Matroids, Part I

8.4 Non Bipartite Matching, Part IV

8.4 Non Bipartite Matching, Part IV

7.4 Total Dual Integrality, Part I

7.4 Total Dual Integrality, Part I

8.11 Weighted Matching, Part III

8.11 Weighted Matching, Part III

8.8 The Matching Polytope, Part III

8.8 The Matching Polytope, Part III

7.3 Total Unimodularity, Part III

7.3 Total Unimodularity, Part III

7.7 r-Arborescences and TDI, Part I

7.7 r-Arborescences and TDI, Part I

7.6 Total Dual Integrality, Part III

7.6 Total Dual Integrality, Part III

8.12 Weighted Matching, Part IV

8.12 Weighted Matching, Part IV

8.10 Weighted Matching, Part II

8.10 Weighted Matching, Part II

9.3 Matroids, Part III

9.3 Matroids, Part III

8.2 Non-Bipartite Matching, Part II

8.2 Non-Bipartite Matching, Part II

9.4 Matroids, Part IV

9.4 Matroids, Part IV

8.3 Non-Bipartite Matching, Part III

8.3 Non-Bipartite Matching, Part III

7.5 Total Dual Integrality, Part II

7.5 Total Dual Integrality, Part II

8.1 Non-Bipartite Matching, Part I

8.1 Non-Bipartite Matching, Part I

8.7 The Matching Polytope, Part II

8.7 The Matching Polytope, Part II

9.7 Matroids, Part VII

9.7 Matroids, Part VII

9.6 Matroids, Part VI

9.6 Matroids, Part VI

EE362K week 1 2015S

EE362K week 1 2015S

EE362K week 2 2015S

EE362K week 2 2015S

EE362K week 3 2015S

EE362K week 3 2015S

EE362K week 4 2015S

EE362K week 4 2015S

EE362K Week 6 2015S

EE362K Week 6 2015S

EE362K week 7 2015S

EE362K week 7 2015S

EE362K week 8 2015S

EE362K week 8 2015S

EE362K Week 9 2015S

EE362K Week 9 2015S

EE362K Week 10 2015S

EE362K Week 10 2015S

EE362K Week 11 2015S

EE362K Week 11 2015S

Nov 6 part 4

Nov 6 part 4

Nov 6 part 3

Nov 6 part 3

Nov 6 part 2

Nov 6 part 2

Matrix Concentration Lecture Three

Matrix Concentration Lecture Three

Matrix Concentration Lecture Two

Matrix Concentration Lecture Two

Matrix Concentration Lecture One

Matrix Concentration Lecture One

The Power Method

The Power Method

The Lanczos Algorithm, Part 2/2

The Lanczos Algorithm, Part 2/2

The Lanczos Algorithm, Part 1/2

The Lanczos Algorithm, Part 1/2

Some more linear algebra

Some more linear algebra

Solutions to Linear Algebra Qs on Diagnostic Quiz

Solutions to Linear Algebra Qs on Diagnostic Quiz

Solutions to Prob Qs on Diagnostic Quiz

Solutions to Prob Qs on Diagnostic Quiz

LDA Solution

LDA Solution

Nov 6 part 1

Nov 6 part 1