The Chute - Tuckerman Ravine
Andrew Xia
The Chute - Tuckerman Ravine
2:01
Cactus to Clouds --America's best 10,000ft hike?
Andrew Xia
Cactus to Clouds --America's best 10,000ft hike?
5:49
Dynamic Pricing with Bayesian Updates from Online Reviews
Andrew Xia
Dynamic Pricing with Bayesian Updates from Online Reviews
7:08
Santiago Sunset
Andrew Xia
Santiago Sunset
6:01
6.875 (Cryptography) L3: Number Theory
Andrew Xia
6.875 (Cryptography) L3: Number Theory
1:19:30
6.875 (Cryptography) L11: Learning with Errors
Andrew Xia
6.875 (Cryptography) L11: Learning with Errors
1:17:28
6.875 (Cryptography) L12: Zero Knowledge I
Andrew Xia
6.875 (Cryptography) L12: Zero Knowledge I
1:20:52
6.875 (Cryptography) L6: Pseudorandom Generators
Andrew Xia
6.875 (Cryptography) L6: Pseudorandom Generators
1:18:35
6.875 (Cryptography) L10: Public Key Encryption II
Andrew Xia
6.875 (Cryptography) L10: Public Key Encryption II
1:10:49
6.875 (Cryptography) L13: Zero Knowledge II
Andrew Xia
6.875 (Cryptography) L13: Zero Knowledge II
1:23:32
6.875 (Cryptography) L4: Hardcore Bits
Andrew Xia
6.875 (Cryptography) L4: Hardcore Bits
1:23:10
6.875 (Cryptography) L9: Public Key Encryption
Andrew Xia
6.875 (Cryptography) L9: Public Key Encryption
1:17:40
6.875 (Cryptography) L8: Trapdoor Functions
Andrew Xia
6.875 (Cryptography) L8: Trapdoor Functions
1:19:56
6.875 (Cryptography) L7: Pseudorandom Functions
Andrew Xia
6.875 (Cryptography) L7: Pseudorandom Functions
1:21:25
6.875 (Cryptography) L5: Hardcore Bits II
Andrew Xia
6.875 (Cryptography) L5: Hardcore Bits II
1:05:11
6.875 (Cryptography) L20: Garbled Circuits
Andrew Xia
6.875 (Cryptography) L20: Garbled Circuits
1:20:06
6.875 (Cryptography) L14: Zero Knolwedge Proofs in NP
Andrew Xia
6.875 (Cryptography) L14: Zero Knolwedge Proofs in NP
1:20:08
6.875 (Cryptography) L22: MPC in the Malicious Setting
Andrew Xia
6.875 (Cryptography) L22: MPC in the Malicious Setting
1:10:28
6.875 (Cryptography) L15: Message Authentication Codes, Digital Signatures
Andrew Xia
6.875 (Cryptography) L15: Message Authentication Codes, Digital Signatures
1:21:46
6.875 (Cryptography) L21: BGW MPC, Malicious Adversaries
Andrew Xia
6.875 (Cryptography) L21: BGW MPC, Malicious Adversaries
1:23:48
6.875 (Cryptography) L17: Hash Functions, Random Oracles
Andrew Xia
6.875 (Cryptography) L17: Hash Functions, Random Oracles
1:19:53
6.875 (Cryptography) L24: Fully Homomorphic Encryption II, Private Information Retrieval
Andrew Xia
6.875 (Cryptography) L24: Fully Homomorphic Encryption II, Private Information Retrieval
1:20:10
6.875 (Cryptogaphy) L19: Oblivious Transfer, Two Party Computation
Andrew Xia
6.875 (Cryptogaphy) L19: Oblivious Transfer, Two Party Computation
1:23:33
6.875 (Cryptography) L16: MACs, Digital Signatures
Andrew Xia
6.875 (Cryptography) L16: MACs, Digital Signatures
1:21:23
6.875 (Cryptography) L23: Fully Homomorphic Encryption I
Andrew Xia
6.875 (Cryptography) L23: Fully Homomorphic Encryption I
1:22:47
6.875 (Cryptography) L2: One-Way Functions
Andrew Xia
6.875 (Cryptography) L2: One-Way Functions
1:20:56
6.875 (Cryptography) L1: Introduction, One-Time Pad
Andrew Xia
6.875 (Cryptography) L1: Introduction, One-Time Pad
1:20:45
DJI Mavic Around Facebook
Andrew Xia
DJI Mavic Around Facebook
2:55
Denver Landing Timelapse
Andrew Xia
Denver Landing Timelapse
1:15
NO SERVICE: Canal to Chambers
Andrew Xia
NO SERVICE: Canal to Chambers
5:27
Chiang Mai and Pai
Andrew Xia
Chiang Mai and Pai
7:41
Visiting the MTA Transit Museum
Andrew Xia
Visiting the MTA Transit Museum
18:29
Tokyo, the Third Time (ft. MUSCAT Program)
Andrew Xia
Tokyo, the Third Time (ft. MUSCAT Program)
9:51
Two Days in Bangkok
Andrew Xia
Two Days in Bangkok
3:13
30 Hours to Thailand
Andrew Xia
30 Hours to Thailand
3:11
6.115 Final Project: 3D Tic Tac Toe AI
Andrew Xia
6.115 Final Project: 3D Tic Tac Toe AI
1:12
MIT 6.854 Spring 2016 Lecture 25: Course Summary
Andrew Xia
MIT 6.854 Spring 2016 Lecture 25: Course Summary
1:15:09
MIT 6.854 Spring 2016 Lecture 24: Oblivious Subspace Embeddings
Andrew Xia
MIT 6.854 Spring 2016 Lecture 24: Oblivious Subspace Embeddings
1:11:36
MIT 6.854 Spring 2016 Lecture 22: Compressed Sensing
Andrew Xia
MIT 6.854 Spring 2016 Lecture 22: Compressed Sensing
1:18:32
MIT 6.854 Spring 2016 Lecture 23: Smoothed Analysis
Andrew Xia
MIT 6.854 Spring 2016 Lecture 23: Smoothed Analysis
1:24:05
MIT 6.854 Spring 2016 Lecture 21: Planted Clique and Random Matrix Theory
Andrew Xia
MIT 6.854 Spring 2016 Lecture 21: Planted Clique and Random Matrix Theory
1:18:35
MIT 6.854 Spring 2016 Lecture 20: Grothendieck's Inequality and the Lovasz Theta Function
Andrew Xia
MIT 6.854 Spring 2016 Lecture 20: Grothendieck's Inequality and the Lovasz Theta Function
1:10:37
MIT 6.854 Spring 2016 Lecture 17: Multiplicative Weights and Zero Sum Games
Andrew Xia
MIT 6.854 Spring 2016 Lecture 17: Multiplicative Weights and Zero Sum Games
1:08:38
MIT 6.854 Spring 2016 Lecture 19: Semidefinite Programming, MAXCUT
Andrew Xia
MIT 6.854 Spring 2016 Lecture 19: Semidefinite Programming, MAXCUT
1:15:42
MIT 6.854 Spring 2016 Lecture 18: Applications of Multiplicative Weights
Andrew Xia
MIT 6.854 Spring 2016 Lecture 18: Applications of Multiplicative Weights
1:17:34
MIT 6.854 Spring 2016 Lecture 16: Interior Point Methods
Andrew Xia
MIT 6.854 Spring 2016 Lecture 16: Interior Point Methods
1:24:36
MIT 6.854 Spring 2016 Lecture 15: Gradient Descent
Andrew Xia
MIT 6.854 Spring 2016 Lecture 15: Gradient Descent
1:14:11
MIT 6.854 Spring 2016 Lecture 14: Rounding Linear Programming Relaxations
Andrew Xia
MIT 6.854 Spring 2016 Lecture 14: Rounding Linear Programming Relaxations
1:19:03
MIT 6.854 Spring 2016 Lecture 8: Capacity Scaling and Min Cost Matching
Andrew Xia
MIT 6.854 Spring 2016 Lecture 8: Capacity Scaling and Min Cost Matching
1:20:53
MIT 6.854 Spring 2016 Lecture 13: Submodular Functions
Andrew Xia
MIT 6.854 Spring 2016 Lecture 13: Submodular Functions
1:06:59
MIT 6.854 Spring 2016 Lecture 12: From Separation to Optimization and Back; Ellipsoid Method
Andrew Xia
MIT 6.854 Spring 2016 Lecture 12: From Separation to Optimization and Back; Ellipsoid Method
1:18:23
MIT 6.854 Spring 2016 Lecture 10: Introduction to Linear Programming
Andrew Xia
MIT 6.854 Spring 2016 Lecture 10: Introduction to Linear Programming
1:15:51
MIT 6.854 Spring 2016 Lecture 11: Strong Duality, Zero Sum Games and Complementary Slackness
Andrew Xia
MIT 6.854 Spring 2016 Lecture 11: Strong Duality, Zero Sum Games and Complementary Slackness
1:17:08
MIT 6.854 Spring 2016 Lecture 9: Min Cost Flow, Goldberg-Tarjan
Andrew Xia
MIT 6.854 Spring 2016 Lecture 9: Min Cost Flow, Goldberg-Tarjan
1:19:15
MIT 6.854 Spring 2016 Lecture 7: Flow Decomposition and Augmenting Paths
Andrew Xia
MIT 6.854 Spring 2016 Lecture 7: Flow Decomposition and Augmenting Paths
1:13:40
MIT 6.854 Spring 2016 Lecture 6: Nearest Neighbor Search and LSH
Andrew Xia
MIT 6.854 Spring 2016 Lecture 6: Nearest Neighbor Search and LSH
1:20:51
MIT 6.854 Spring 2016 Lecture 3 part 2
Andrew Xia
MIT 6.854 Spring 2016 Lecture 3 part 2
20:12
MIT 6.854 Spring 2016 Lecture 5: Johnson Lindenstrauss Lemma and Extensions
Andrew Xia
MIT 6.854 Spring 2016 Lecture 5: Johnson Lindenstrauss Lemma and Extensions
1:17:54
MIT 6.854 Spring 2016 Lecture 4: Distinct Elements and Heavy Hitters
Andrew Xia
MIT 6.854 Spring 2016 Lecture 4: Distinct Elements and Heavy Hitters
1:19:54
MIT 6.854 Spring 2016 Lecture 3: Consistent Hashing and Random Trees
Andrew Xia
MIT 6.854 Spring 2016 Lecture 3: Consistent Hashing and Random Trees
59:17