Ph.D. Dissertations - Luca Trevisan

Approximation and Hardness: Beyond P and NP
Pasin Manurangsi [2019]

Efficient learning algorithms with limited information
Anindya De [2013]

The Computational Complexity of Randomness
Thomas Watson [2013]

Limitations of Linear and Semidefinite Programs
Grant Robert Schoenebeck [2010]

Pseudorandomness against Depth-2 Circuits and Analysis of Goldreich's Candidate One-Way Function
Seyed Omid Etesami [2010]

Local Constraints in Combinatorial Optimization
Madhur Tulsiani [2009]

Black-Box Complexity of Encryption and Commitment
Hoe Teck Wee [2007]

Local Computation and Reducibility
Kenji Christopher Obata [2006]

The Relation Between Worst Case and Average Case Complexity for NP
Andrej Bogdanov [2005]