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On the Round Complexity Landscape of Secure Multi-party Computation
In secure multi-party computation (MPC), n parties wish to jointly perform a computation on their private inputs in a secure way, so that no adversary corrupting a subset of the parties can learn more information than their ...
Expanders in Arithmetic Circuit Lower Bound : Towards a Separation Between ROABPs and Multilinear Depth 3 Circuits
Consider the problem of Polynomial Identity Testing(PIT): we are given an arithmetic circuit
computing a multivariate polynomial over some eld and we have to determine whether that
polynomial is identically zero or not. ...
Hypergraph Network Models: Learning, Prediction, and Representation in the Presence of Higher-Order Relations
The very thought about “relating” objects makes us assume the relation would be “pairwise”, and
not of a “higher-order” — involving possibly more than two of them at a time. Yet in reality,
higher-order relations do exist ...
Constant-rate Non-malleable Codes and their Applications
Non-malleable codes(NMC) introduced by Dziembowski, Pietrzak and Wichs in ITCS 2010,
provide powerful security guarantees where error-correcting codes can not provide any guarantee: a decoding of tampered codeword is ...
Efficient Schemes for Partitioning Based Scheduling of Real-Time Tasks in Multicore Architecture
The correctness of hard real-time systems depends not only on its logical correctness but also, on its ability to meet all its deadline. Existing real-time systems use either a pure real-time scheduler or a real-time ...
P3 : An Effective Technique for Partitioned Path Profiling
Acyclic path profile is an abstraction of dynamic control flow paths of procedures and
has been found to be useful in a wide spectrum of activities. Unfortunately, the runtime
overhead of obtaining such a profile can be ...
Modeling and Adaptive Scheduling Strategies for Distributed Graph Algorithms
Graph processing at scales of millions-billions of vertices and edges has become common to solve
real-world problems in domains like social networks, smart cities and genomics. Distributed
"Big Data" platforms for graph ...
Decision Making under Uncertainty : Reinforcement Learning Algorithms and Applications in Cloud Computing, Crowdsourcing and Predictive Analytics
In this thesis, we study both theoretical and practical aspects of decision making, with a focus on reinforcement learning based methods. Reinforcement learning (RL) is a form of semi-supervised learning in which the agent ...
Model Checking Temporal Properties of Presburger Counter Systems
Counter systems are a well-known and powerful modeling notation for specifying infnite state systems. In this thesis we target the problem of checking temporal properties of
counter systems. We address three predominant ...
Model Extraction Defense using Modified Variational Autoencoder
Machine Learning as a Service (MLaaS) exposes machine learning (ML) models that are trained on confidential datasets to users in the form of an Application Programming Interface (API). Since the MLaaS models are deployed ...