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Atri Rudra

Publications and source records attributed to Atri Rudra.

63 records · Page 4Linked to original sources
arXiv2012

Worst-case Optimal Join Algorithms

Efficient join processing is one of the most fundamental and well-studied tasks in database research. In this work, we examine algorithms for natural join queries over many relations and describe a novel algorithm to process these queries optimally in terms of worst-case data complexity. Our result builds on recent work by Atserias, Grohe, and Marx, who gave bounds on the size of a full conjunctive query in terms of the sizes of the individual relations in the body of the query. These bounds, however, are not constructive: they rely on Shearer's entropy inequality which is information-theoretic. Thus, the previous results leave open the question of whether there exist algorithms whose running time achieve these optimal bounds. An answer to this question may be interesting to database practice, as it is known that any algorithm based on the traditional select-project-join style plans typically employed in an RDBMS are asymptotically slower than the optimal for some queries. We construct an algorithm whose running time is worst-case optimal for all natural join queries. Our result may be of independent interest, as our algorithm also yields a constructive proof of the general fractional cover bound by Atserias, Grohe, and Marx without using Shearer's inequality. This bound implies two famous inequalities in geometry: the Loomis-Whitney inequality and the Bollobás-Thomason inequality. Hence, our results algorithmically prove these inequalities as well. Finally, we discuss how our algorithm can be used to compute a relaxed notion of joins.

cs.DB↗
arXiv2012

Simulating Special but Natural Quantum Circuits

We identify a sub-class of BQP that captures certain structural commonalities among many quantum algorithms including Shor's algorithms. This class does not contain all of BQP (e.g. Grover's algorithm does not fall into this class). Our main result is that any algorithm in this class that measures at most O(log n) qubits can be simulated by classical randomized polynomial time algorithms. This does not dequantize Shor's algorithm (as the latter measures n qubits) but our work also highlights a new potentially hard function for cryptographic applications. Our main technical contribution is (to the best of our knowledge) a new exact characterization of certain sums of Fourier-type coefficients (with exponentially many summands).

cs.CC↗
arXiv2011

An FPTAS for the Lead-Based Multiple Video Transmission LMVT Problem

The Lead-Based Multiple Video Transmission (LMVT) problem is motivated by applications in managing the quality of experience (QoE) of video streaming for mobile clients. In an earlier work, the LMVT problem has been shown to be NP-hard for a specific bit-to-lead conversion function $ϕ$. In this work, we show the problem to be NP-hard even if the function $ϕ$ is linear. We then design a fully polynomial time approximation scheme (FPTAS) for the problem. This problem is exactly equivalent to the Santa Clause Problem on which there has been a lot of work done off-late.

cs.DS↗
arXiv2011

Storage Enforcement with Kolmogorov Complexity and List Decoding

We consider the following problem that arises in outsourced storage: a user stores her data $x$ on a remote server but wants to audit the server at some later point to make sure it actually did store $x$. The goal is to design a (randomized) verification protocol that has the property that if the server passes the verification with some reasonably high probability then the user can rest assured that the server is storing $x$. In this work we present an optimal solution (in terms of the user's storage and communication) while at the same time ensuring that a server that passes the verification protocol with any reasonable probability will store, to within a small \textit{additive} factor, $C(x)$ bits of information, where $C(x)$ is the plain Kolmogorov complexity of $x$. (Since we cannot prevent the server from compressing $x$, $C(x)$ is a natural upper bound.) The proof of security of our protocol combines Kolmogorov complexity with list decoding and unlike previous work that relies upon cryptographic assumptions, we allow the server to have unlimited computational power. To the best of our knowledge, this is the first work that combines Kolmogorov complexity and list decoding. Our framework is general enough to capture extensions where the user splits up $x$ and stores the fragment across multiple servers and our verification protocol can handle non-responsive servers and colluding servers. As a by-product, we also get a proof of retrievability. Finally, our results also have an application in `storage enforcement' schemes, which in turn have an application in trying to update a remote server that is potentially infected with a virus.

cs.CC↗
arXiv2010

When LP is the Cure for Your Matching Woes: Improved Bounds for Stochastic Matchings

Consider a random graph model where each possible edge $e$ is present independently with some probability $p_e$. Given these probabilities, we want to build a large/heavy matching in the randomly generated graph. However, the only way we can find out whether an edge is present or not is to query it, and if the edge is indeed present in the graph, we are forced to add it to our matching. Further, each vertex $i$ is allowed to be queried at most $t_i$ times. How should we adaptively query the edges to maximize the expected weight of the matching? We consider several matching problems in this general framework (some of which arise in kidney exchanges and online dating, and others arise in modeling online advertisements); we give LP-rounding based constant-factor approximation algorithms for these problems. Our main results are the following: We give a 4 approximation for weighted stochastic matching on general graphs, and a 3 approximation on bipartite graphs. This answers an open question from [Chen etal ICALP 09]. Combining our LP-rounding algorithm with the natural greedy algorithm, we give an improved 3.46 approximation for unweighted stochastic matching on general graphs. We introduce a generalization of the stochastic online matching problem [Feldman etal FOCS 09] that also models preference-uncertainty and timeouts of buyers, and give a constant factor approximation algorithm.

cs.DS↗
arXiv2010

Data Stream Algorithms for Codeword Testing

Motivated by applications in storage systems and property testing, we study data stream algorithms for local testing and tolerant testing of codes. Ideally, we would like to know whether there exist asymptotically good codes that can be local/tolerant tested with one-pass, poly-log space data stream algorithms. We show that for the error detection problem (and hence, the local testing problem), there exists a one-pass, log-space data stream algorithm for a broad class of asymptotically good codes, including the Reed-Solomon (RS) code and expander codes. In our technically more involved result, we give a one-pass, $O(e\log^2{n})$-space algorithm for RS (and related) codes with dimension $k$ and block length $n$ that can distinguish between the cases when the Hamming distance between the received word and the code is at most $e$ and at least $a\cdot e$ for some absolute constant $a>1$. For RS codes with random errors, we can obtain $e\le O(n/k)$. For folded RS codes, we obtain similar results for worst-case errors as long as $e\le (n/k)^{1-\eps}$ for any constant $\eps>0$. These results follow by reducing the tolerant testing problem to the error detection problem using results from group testing and the list decodability of the code. We also show that using our techniques, the space requirement and the upper bound of $e\le O(n/k)$ cannot be improved by more than logarithmic factors.

cs.IT↗
arXiv2010

Two Theorems in List Decoding

We prove the following results concerning the list decoding of error-correcting codes: (i) We show that for \textit{any} code with a relative distance of $δ$ (over a large enough alphabet), the following result holds for \textit{random errors}: With high probability, for a $ρ\le δ-\eps$ fraction of random errors (for any $\eps>0$), the received word will have only the transmitted codeword in a Hamming ball of radius $ρ$ around it. Thus, for random errors, one can correct twice the number of errors uniquely correctable from worst-case errors for any code. A variant of our result also gives a simple algorithm to decode Reed-Solomon codes from random errors that, to the best of our knowledge, runs faster than known algorithms for certain ranges of parameters. (ii) We show that concatenated codes can achieve the list decoding capacity for erasures. A similar result for worst-case errors was proven by Guruswami and Rudra (SODA 08), although their result does not directly imply our result. Our results show that a subset of the random ensemble of codes considered by Guruswami and Rudra also achieve the list decoding capacity for erasures. Our proofs employ simple counting and probabilistic arguments.

cs.IT↗
arXiv2007

Explicit Codes Achieving List Decoding Capacity: Error-correction with Optimal Redundancy

We present error-correcting codes that achieve the information-theoretically best possible trade-off between the rate and error-correction radius. Specifically, for every $0 < R < 1$ and $\eps> 0$, we present an explicit construction of error-correcting codes of rate $R$ that can be list decoded in polynomial time up to a fraction $(1-R-\eps)$ of {\em worst-case} errors. At least theoretically, this meets one of the central challenges in algorithmic coding theory. Our codes are simple to describe: they are {\em folded Reed-Solomon codes}, which are in fact {\em exactly} Reed-Solomon (RS) codes, but viewed as a code over a larger alphabet by careful bundling of codeword symbols. Given the ubiquity of RS codes, this is an appealing feature of our result, and in fact our methods directly yield better decoding algorithms for RS codes when errors occur in {\em phased bursts}. The alphabet size of these folded RS codes is polynomial in the block length. We are able to reduce this to a constant (depending on $\eps$) using ideas concerning ``list recovery'' and expander-based codes from \cite{GI-focs01,GI-ieeejl}. Concatenating the folded RS codes with suitable inner codes also gives us polynomial time constructible binary codes that can be efficiently list decoded up to the Zyablov bound, i.e., up to twice the radius achieved by the standard GMD decoding of concatenated codes.

cs.IT↗