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Electronic Colloquium on Computational Complexity

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All reports by Author Justin Thaler:

TR17-051 | 16th March 2017
Mark Bun, Justin Thaler

A Nearly Optimal Lower Bound on the Approximate Degree of AC$^0$

The approximate degree of a Boolean function $f \colon \{-1, 1\}^n \rightarrow \{-1, 1\}$ is the least degree of a real polynomial that approximates $f$ pointwise to error at most $1/3$. We introduce a generic method for increasing the approximate degree of a given function, while preserving its computability by ... more >>>

TR16-140 | 9th September 2016
Adam Bouland, Lijie Chen, Dhiraj Holden, Justin Thaler, Prashant Nalini Vasudevan

On SZK and PP

Revisions: 3

In both query and communication complexity, we give separations between the class NISZK, containing those problems with non-interactive statistical zero knowledge proof systems, and the class UPP, containing those problems with randomized algorithms with unbounded error. These results significantly improve on earlier query separations of Vereschagin [Ver95] and Aaronson [Aar12] ... more >>>

TR16-121 | 4th August 2016
Mark Bun, Justin Thaler

Approximate Degree and the Complexity of Depth Three Circuits

Revisions: 1

Threshold weight, margin complexity, and Majority-of-Threshold circuit size are basic complexity measures of Boolean functions that arise in learning theory, communication complexity, and circuit complexity. Each of these measures might exhibit a chasm at depth three: namely, all polynomial size Boolean circuits of depth two have polynomial complexity under the ... more >>>

TR16-075 | 9th May 2016
Mark Bun, Justin Thaler

Improved Bounds on the Sign-Rank of AC$^0$

Revisions: 1

The sign-rank of a matrix $A$ with entries in $\{-1, +1\}$ is the least rank of a real matrix $B$ with $A_{ij} \cdot B_{ij} > 0$ for all $i, j$. Razborov and Sherstov (2008) gave the first exponential lower bounds on the sign-rank of a function in AC$^0$, answering an ... more >>>

TR15-041 | 25th March 2015
Mark Bun, Justin Thaler

Dual Polynomials for Collision and Element Distinctness

The approximate degree of a Boolean function $f: \{-1, 1\}^n \to \{-1, 1\}$ is the minimum degree of a real polynomial that approximates $f$ to within error $1/3$ in the $\ell_\infty$ norm. In an influential result, Aaronson and Shi (J. ACM 2004) proved tight $\tilde{\Omega}(n^{1/3})$ and $\tilde{\Omega}(n^{2/3})$ lower bounds on ... more >>>

TR14-150 | 10th November 2014
Justin Thaler

Lower Bounds for the Approximate Degree of Block-Composed Functions

Revisions: 3

We describe a new hardness amplification result for point-wise approximation of Boolean functions by low-degree polynomials. Specifically, for any function $f$ on $N$ bits, define $F(x_1, \dots, x_M) = \text{OMB}(f(x_1), \dots, f(x_M))$ to be the function on $M \cdot N$ bits obtained by block-composing $f$ with a specific DNF known ... more >>>

TR14-090 | 11th July 2014
Justin Thaler

Semi-Streaming Algorithms for Annotated Graph Streams

Revisions: 2

Considerable effort has been devoted to the development of streaming algorithms for analyzing massive graphs. Unfortunately, many results have been negative, establishing that a wide variety of problems require $\Omega(n^2)$ space to solve. One of the few bright spots has been the development of semi-streaming algorithms for a handful of ... more >>>

TR14-086 | 11th July 2014
Amit Chakrabarti, Graham Cormode, Andrew McGregor, Justin Thaler, Suresh Venkatasubramanian

Verifiable Stream Computation and Arthur–Merlin Communication

In the setting of streaming interactive proofs (SIPs), a client (verifier) needs to compute a given function on a massive stream of data, arriving online, but is unable to store even a small fraction of the data. It outsources the processing to a third party service (prover), but is unwilling ... more >>>

TR13-180 | 17th December 2013
Amit Chakrabarti, Graham Cormode, Andrew McGregor, Justin Thaler, Suresh Venkatasubramanian

On Interactivity in Arthur-Merlin Communication and Stream Computation

Revisions: 1

We introduce {\em online interactive proofs} (OIP), which are a hierarchy of communication complexity models that involve both randomness and nondeterminism (thus, they belong to the Arthur--Merlin family), but are {\em online} in the sense that the basic communication flows from Alice to Bob alone. The complexity classes defined by ... more >>>

TR13-151 | 7th November 2013
Mark Bun, Justin Thaler

Hardness Amplification and the Approximate Degree of Constant-Depth Circuits

Revisions: 3

We establish a generic form of hardness amplification for the approximability of constant-depth Boolean circuits by polynomials. Specifically, we show that if a Boolean circuit cannot be pointwise approximated by low-degree polynomials to within constant error in a certain one-sided sense, then an OR of disjoint copies of that circuit ... more >>>

TR13-032 | 26th February 2013
Mark Bun, Justin Thaler

Dual Lower Bounds for Approximate Degree and Markov-Bernstein Inequalities

Revisions: 2

The $\epsilon$-approximate degree of a Boolean function $f: \{-1, 1\}^n \to \{-1, 1\}$ is the minimum degree of a real polynomial that approximates $f$ to within $\epsilon$ in the $\ell_\infty$ norm. We prove several lower bounds on this important complexity measure by explicitly constructing solutions to the dual of an ... more >>>

TR12-056 | 1st May 2012
Rocco Servedio, Li-Yang Tan, Justin Thaler

Attribute-Efficient Learning and Weight-Degree Tradeoffs for Polynomial Threshold Functions

Revisions: 1

We study the challenging problem of learning decision lists attribute-efficiently, giving both positive and negative results.

Our main positive result is a new tradeoff between the running time and mistake bound for learning length-$k$ decision lists over $n$ Boolean variables. When the allowed running time is relatively high, our new ... more >>>

TR12-022 | 14th March 2012
Amit Chakrabarti, Graham Cormode, Andrew McGregor, Justin Thaler

Annotations in Data Streams

Revisions: 1

The central goal of data stream algorithms is to process massive streams of data using sublinear storage space. Motivated by work in the database community on outsourcing database and data stream processing, we ask whether the space usage of such algorithms can be further reduced by enlisting a more powerful ... more >>>

TR11-105 | 22nd July 2011
Graham Cormode, Michael Mitzenmacher, Justin Thaler

Streaming Graph Computations with a Helpful Advisor

Revisions: 1

Motivated by the trend to outsource work to commercial cloud computing services, we consider a variation of the streaming paradigm where a streaming algorithm can be assisted by a powerful helper that can provide annotations to the data stream. We extend previous work on such annotation models by considering a ... more >>>

TR10-159 | 28th October 2010
Graham Cormode, Justin Thaler, Ke Yi

Verifying Computations with Streaming Interactive Proofs

Applications based on outsourcing computation require guarantees to the data owner that the desired computation has been performed correctly by the service provider. Methods based on proof systems can give the data owner the necessary assurance, but previous work does not give a sufficiently scalable and practical solution, requiring a ... more >>>

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