Theory of Distributed Systems (TDS)

Lewin Tseng: Exact Byzantine Consensus under Local Broadcast Model
Friday, December 13, 2019 - 1:00pm to 2:30pm
Brabeeba Wang: The First at All-Time Convergence Analysis for Biological Oja's Rule to Solve Streaming PCA
Friday, October 11, 2019 - 1:00pm to 2:30pm

Biological Oja’s rule is a biologically feasible algorithm using Hebbian-type local synaptic update that solves the streaming PCA problem.

Counting to Ten with Yael Hitron: Two Fingers: Compressed Counting with Spiking Neurons
Friday, July 26, 2019 - 1:00pm to 2:30pm

We consider the task of measuring time with probabilistic threshold gates implemented by bio-inspired spiking neurons.

Hoa Vu: Toward the Locality of Vizing's Theorem
Friday, November 16, 2018 - 1:00pm to 2:30pm
Siddhartha Jayanti: An Optimal Amortized Algorithm for Abortable Mutual Exclusion
Friday, May 11, 2018 - 1:00pm to 2:00pm
Lewis Tseng: Asynchronous Crash-Tolerant Consensus in Directed Graphs
Friday, March 23, 2018 - 1:00pm to 2:30pm

Consider a directed point-to-point network.

Lili Su: Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent
Friday, December 8, 2017 - 1:00pm to 2:30pm
We consider the distributed statistical learning problem over decentralized systems that are prone to adversarial attacks. This setup arises in many practical applications, including Google’s Federated Learning.
Shlomi Dolev: Encountering Challenges in Computer Science, Including, Quantum Safe Public Key Infrastructure
Thursday, November 9, 2017 - 3:00pm to 4:30pm
 At this presentation, I will give an overview on recent results from my research group on distributed computing, 
Siddhartha Jayanti: Concurrent Disjoint Set Union
Friday, October 27, 2017 - 1:00pm to 2:30pm

A famous result in sequential data structures that the Union-Find object can be implemented in amortized inverse-Ackermann work per operation.

Slobodan Mitrovic: MapReduce and approximate Maximal Matchings
Friday, October 6, 2017 - 1:00pm to 2:30pm
The last decade has witnessed the success of a number of massive parallel computation (MPC) frameworks, such as MapReduce, Hadoop, Dryad, or Spark.


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