Fall 2016
September 8  Prashanth L. A. UMD 
Modelfree optimization of human preferences in stochastic systems
Abstract: In several realworld systems involving humans, traditional expected value cannot explain the observed behavior and incorporating distortions in the underlying probabilities of the system can alleviate this problem. Cumulative prospect theory (CPT) is a very popular approach that is based on probabilistic distortions and is more general than the expected value. We bring this idea to a stochastic optimization framework and propose algorithms for both estimation and optimization of the CPTvalue objective. We propose an empirical distribution function based scheme to estimate the CPTvalue and then use this scheme in the inner loop of a CPTvalue optimization procedure. We propose both gradientbased as well as gradientfree CPTvalue optimization algorithms, that are based on two wellknown simulation optimization ideas: simultaneous perturbation stochastic approximation (SPSA) and modelbased parameter search (MPS), respectively. We provide theoretical convergence guarantees for all the proposed algorithms and also illustrate the usefulness of CPTbased criteria in a traffic signal control application.
The majority of the talk will be accessible to a broad audience. ** Joint work with Cheng Jie, Michael Fu, Steve Marcus and Csaba Szepesvari. 
September 15  Alborz Alavian UMD 
Polynomial Algorithms for LowerBounds on the kth Singular Value of a Polynomial Matrix
Abstract: This talk is on the minimization of the kth singular value of a general polynomial matrix. We will discuss an equivalent optimization problem that is composed of a polynomial objective subjected to polynomial constraints, and a further rank constraint. We will then discuss two methods on the rank constraint to write this problem as a polynomial optimization problem. This can be used in conjunction with SumofSquares (SOS) techniques to derive a lowerbound on the kth singular value of a polynomial matrix. Time allowing, we will discuss applications of this problem in deriving bounds on how far an LTI dynamic system is from loosing decentralized controllability.

September 29  Zitan Chen UMD 
The Capacity of Online (Causal) qary ErrorErasure Channels
Abstract: In the qary online (causal) channel coding model, a sender wishes to communicate a message to a receiver by transmitting a codeword ${\bf x} =(x_1,...,x_n)$ symbolbysymbol via a channel limited to at most np errors (symbol changes) and np* erasures. The channel is ``online'' (i.e., ``causal") in the sense that at the ith step of communication the channel decides whether to corrupt the ith symbol or not only based on its view of the symbols $(x_1,...,x_i)$. This is in contrast to the classical adversarial channel in which the corruption is chosen with full knowledge of the sent codeword ${\bf x}$. The capacities of binary online bitfliponly channels, and separately binary online erasureonly channels have been characterized recently.
In this work we extend prior results in two important ways. First, we obtain the capacity of qary online channels for general $q$ (rather than just $q$=2). Second, we analyze combined errorerasure corruption models (rather than studying them separately). Characterization of this much broader class of symmetric online channels gives a fuller understanding of the effects of causality on jamming adversaries. 
October 6  P. Vijay Kumar IISc and USC 
Binary Codes with Locality for Multiple Erasures Having Short Block Length
Abstract: This paper considers linear, binary codes having locality parameter $r$, that are capable of recovering from $t$ greater than or equal to $2$ erasures and which additionally, possess short block length. The focus is mostly on codes which can recover from multiple erasures in a sequential manner. The case of recovery from multiple erasures in parallel will be discussed, in the restricted setting where the column and row weight of the paritycheck matrix are fixed, and where the parity checks on a code symbol are pairwise orthogonal. This is joint work with S. B. Balaji and K. P. Prasanth.

October 13  Zitan Chen, continued UMD 
The Capacity of Online (Causal) qary ErrorErasure Channels
Abstract: In the qary online (causal) channel coding model, a sender wishes to communicate a message to a receiver by transmitting a codeword ${\bf x} =(x_1,...,x_n)$ symbolbysymbol via a channel limited to at most np errors (symbol changes) and np* erasures. The channel is ``online'' (i.e., ``causal") in the sense that at the ith step of communication the channel decides whether to corrupt the ith symbol or not only based on its view of the symbols $(x_1,...,x_i)$. This is in contrast to the classical adversarial channel in which the corruption is chosen with full knowledge of the sent codeword ${\bf x}$. The capacities of binary online bitfliponly channels, and separately binary online erasureonly channels have been characterized recently.
In this work we extend prior results in two important ways. First, we obtain the capacity of qary online channels for general $q$ (rather than just $q$=2). Second, we analyze combined errorerasure corruption models (rather than studying them separately). Characterization of this much broader class of symmetric online channels gives a fuller understanding of the effects of causality on jamming adversaries. 
October 20  Vinay Praneeth Boda UMD 
Sampling Rate Distortion
Abstract: In this talk, we consider a discrete memoryless multiple source with $m$ components of which $k \leq m$ possibly different sources are sampled at each time instant and jointly compressed in order to reconstruct all the $m$ sources under a given distortion criterion. A new notion of sampling rate distortion function(SRDf) is introduced, and is characterized first for the case of fixedset sampling.
Next, different forms of randomized sampling in their increasing order of complexity are introduced and their corresponding SRDfs are characterized. For independent random sampling performed without knowledge of the source outputs, it is shown that the SRDf is the same regardless of whether or not the decoder is informed of the sequence of sampled sets. Next, for memoryless random sampling, where the sampling can depend on the source outputs, it is shown that deterministic sampling, characterized by a conditional pointmass, is optimal and suffices to achieve the sampling rate distortion function. This is joint work with Prof. Prakash Narayan. 
October 27  Yingquan Wu Micron Technology 
LDPC for flash  from theory to practice
Abstract: This talk first presents the challenges of errorcorrecting coding in flash memories. It then gives the practical overview of LDPC codes. Finally, it reveals some insights of LDPC optimization for flash memories.

November 3  Paul Cuff Princeton University 
TBA
Abstract: TBA

November 10  Dipankar Maity UMD 
TBA
Abstract: TBA

November 17  Ahmed Arafa UMD 
TBA
Abstract: TBA

December 8  Himanshu Tyagi IISc 
TBA
Abstract: TBA

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Alexander Barg, Prakash Narayan, Vinay Praneeth Boda @umd.edu