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Michael T. Goodrich

Bio: Michael T. Goodrich is an academic researcher from University of California, Irvine. The author has contributed to research in topics: Planar graph & Parallel algorithm. The author has an hindex of 61, co-authored 430 publications receiving 14045 citations. Previous affiliations of Michael T. Goodrich include New York University & Technion – Israel Institute of Technology.


Papers
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Book ChapterDOI
26 Sep 2016
TL;DR: This work presents and analyzes an efficient hash table data structure that simultaneously achieves the following properties: it is based on the classic linear probing collision-handling scheme, it is weakly history-independent, and it is secure against collision-timing attacks.
Abstract: Direct-recording electronic (DRE) voting systems have been used in several countries including United States, India, and the Netherlands to name a few. A common flaw that was discovered by the security researchers was that the votes were stored sequentially according to the time they were cast, which allows an attacker to break the anonymity of the voters. Subsequent research pointed out the connection between vote storage and the privacy property history-independence. In a weakly history-independent data structure, every possible sequence of operations consistent with the current set of items is equally likely to have occurred. In a strongly history-independent data structure, items must be stored in a canonical way, i.e., for any set of items, there is only one possible memory representation. Strong history-independence implies weak history-independence but considerably constrains the design choices of the data structures. In this work, we present and analyze an efficient hash table data structure that simultaneously achieves the following properties: It is based on the classic linear probing collision-handling scheme. It is weakly history-independent. It is secure against collision-timing attacks. That is, we consider adversaries that can measure the time for an update operation, but cannot observe data values, and we show that those adversaries cannot learn information about the items in the table. All operations are significantly faster in practice (almost 2x faster for high load factors) than those of the commonly used strongly history-independent linear probing method proposed by Blelloch and Golovin (FOCS’07), which is not secure against collision-timing attacks.

2 citations

Journal ArticleDOI
TL;DR: This paper presents a competitive analysis for the Start-Gap wear-leveling algorithm, showing that under reasonable assumptions about the sequence of update operations, the Start theGap algorithm has a competitive ratio of 1 / ( 1 − o ( 1 ) ) .

2 citations

Book
01 Jan 2002
TL;DR: A Group-Theoretic Method for Drawing Graphs Symmetrically and some Applications of Orderly Spanning Trees in Graph Drawing.
Abstract: Papers.- Sketch-Driven Orthogonal Graph Drawing.- Maintaining the Mental Map for Circular Drawings.- Graphs, They Are Changing.- Drawing Graphs on Two and Three Lines.- Path-Width and Three-Dimensional Straight-Line Grid Drawings of Graphs.- Drawing Outer-Planar Graphs in O(n log n )Area.- Computing Labeled Orthogonal Drawings.- Computing and Drawing Isomorphic Subgraphs.- A Group-Theoretic Method for Drawing Graphs Symmetrically.- A Branch-and-Cut Approach to the Directed Acyclic Graph Layering Problem.- Geometric Systems of Disjoint Representatives.- An Efficient Fixed Parameter Tractable Algorithm for 1-Sided Crossing Minimization.- Simple and Efficient Bilayer Cross Counting.- Orthogonal 3D Shapes of Theta Graphs.- Separating Thickness from Geometric Thickness.- Book Embeddings and Point-Set Embeddings of Series-Parallel Digraphs.- Compact Encodings of Planar Orthogonal Drawings.- Fractional Lengths and Crossing Numbers.- Drawing Directed Graphs Using One-Dimensional Optimization.- Graph Drawing by High-Dimensional Embedding.- Advances in C-Planarity Testing of Clustered Graphs.- HGV: A Library for Hierarchies, Graphs, and Views.- Rectangular Drawings of Planar Graphs.- Extended Rectangular Drawings of Plane Graphs with Designated Corners.- RINGS: A Technique for Visualizing Large Hierarchies.- Applying Crossing Reduction Strategies to Layered Compound Graphs.- Crossing Reduction by Windows Optimization.- Geometric Graphs with No Self-intersecting Path of Length Three.- Two New Heuristics for Two-Sided Bipartite Graph Drawing.- Straight-Line Drawings of Binary Trees with Linear Area and Arbitrary Aspect Ratio.- Some Applications of Orderly Spanning Trees in Graph Drawing.- Improving Walker's Algorithm to Run in Linear Time.- Semi-dynamic Orthogonal Drawings of Planar Graphs.- Software Demonstrations.- Graph Layout for Workflow Applications with ILOG JViews.- InterViewer: Dynamic Visualization of Protein-Protein Interactions.- Some Modifications of Sugiyama Approach.- A Framework for Complexity Management in Graph Visualization.- A Partitioned Approach to Protein Interaction Mapping.- Camera Position Reconstruction and Tight Direction Networks.- Demonstration of a Preprocessor for the Spring Embedder.- Graph Drawing Contest.- Graph-Drawing Contest Report.- Invited Talks.- Techniques for Interactive Graph Drawing.- Drawing Venn Diagrams.

2 citations

Posted Content
TL;DR: This work believes it is the first to study the exact-learning query complexity for string reconstruction using jumbled-index queries, which are a "mixed-up" typeA of query that have received much attention of late.
Abstract: We study the query complexity of exactly reconstructing a string from adaptive queries, such as substring, subsequence, and jumbled-index queries. Such problems have applications, e.g., in computational biology. We provide a number of new and improved bounds for exact string reconstruction for settings where either the string or the queries are "mixed-up". For example, we show that a periodic (i.e., "mixed-up") string, $S=p^kp'$, of smallest period $p$, where $|p'|<|p|$, can be reconstructed using $O(\sigma|p|+\lg n)$ substring queries, where $\sigma$ is the alphabet size, if $n=|S|$ is unknown. We also show that we can reconstruct $S$ after having been corrupted by a small number of errors $d$, measured by Hamming distance. In this case, we give an algorithm that uses $O(d\sigma|p| + d|p|\lg \frac{n}{d+1})$ queries. In addition, we show that a periodic string can be reconstructed using $2\sigma\lceil\lg n\rceil + 2|p|\lceil\lg \sigma\rceil$ subsequence queries, and that general strings can be reconstructed using $2\sigma\lceil\lg n\rceil + n\lceil\lg \sigma\rceil$ subsequence queries, without knowledge of $n$ in advance. This latter result improves the previous best, decades-old result, by Skiena and Sundaram. Finally, we believe we are the first to study the exact-learning query complexity for string reconstruction using jumbled-index queries, which are a "mixed-up" typeA of query that have received much attention of late.

1 citations


Cited by
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Journal ArticleDOI

[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Proceedings ArticleDOI
22 Jan 2006
TL;DR: Some of the major results in random graphs and some of the more challenging open problems are reviewed, including those related to the WWW.
Abstract: We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

7,116 citations

MonographDOI
01 Jan 2006
TL;DR: This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms, into planning under differential constraints that arise when automating the motions of virtually any mechanical system.
Abstract: Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms. The treatment is centered on robot motion planning but integrates material on planning in discrete spaces. A major part of the book is devoted to planning under uncertainty, including decision theory, Markov decision processes, and information spaces, which are the “configuration spaces” of all sensor-based planning problems. The last part of the book delves into planning under differential constraints that arise when automating the motions of virtually any mechanical system. Developed from courses taught by the author, the book is intended for students, engineers, and researchers in robotics, artificial intelligence, and control theory as well as computer graphics, algorithms, and computational biology.

6,340 citations

Journal ArticleDOI
TL;DR: An overview of the Internet of Things with emphasis on enabling technologies, protocols, and application issues, and some of the key IoT challenges presented in the recent literature are provided and a summary of related research work is provided.
Abstract: This paper provides an overview of the Internet of Things (IoT) with emphasis on enabling technologies, protocols, and application issues. The IoT is enabled by the latest developments in RFID, smart sensors, communication technologies, and Internet protocols. The basic premise is to have smart sensors collaborate directly without human involvement to deliver a new class of applications. The current revolution in Internet, mobile, and machine-to-machine (M2M) technologies can be seen as the first phase of the IoT. In the coming years, the IoT is expected to bridge diverse technologies to enable new applications by connecting physical objects together in support of intelligent decision making. This paper starts by providing a horizontal overview of the IoT. Then, we give an overview of some technical details that pertain to the IoT enabling technologies, protocols, and applications. Compared to other survey papers in the field, our objective is to provide a more thorough summary of the most relevant protocols and application issues to enable researchers and application developers to get up to speed quickly on how the different protocols fit together to deliver desired functionalities without having to go through RFCs and the standards specifications. We also provide an overview of some of the key IoT challenges presented in the recent literature and provide a summary of related research work. Moreover, we explore the relation between the IoT and other emerging technologies including big data analytics and cloud and fog computing. We also present the need for better horizontal integration among IoT services. Finally, we present detailed service use-cases to illustrate how the different protocols presented in the paper fit together to deliver desired IoT services.

6,131 citations

Journal ArticleDOI
TL;DR: This work presents a simple and efficient implementation of Lloyd's k-means clustering algorithm, which it calls the filtering algorithm, and establishes the practical efficiency of the algorithm's running time.
Abstract: In k-means clustering, we are given a set of n data points in d-dimensional space R/sup d/ and an integer k and the problem is to determine a set of k points in Rd, called centers, so as to minimize the mean squared distance from each data point to its nearest center. A popular heuristic for k-means clustering is Lloyd's (1982) algorithm. We present a simple and efficient implementation of Lloyd's k-means clustering algorithm, which we call the filtering algorithm. This algorithm is easy to implement, requiring a kd-tree as the only major data structure. We establish the practical efficiency of the filtering algorithm in two ways. First, we present a data-sensitive analysis of the algorithm's running time, which shows that the algorithm runs faster as the separation between clusters increases. Second, we present a number of empirical studies both on synthetically generated data and on real data sets from applications in color quantization, data compression, and image segmentation.

5,288 citations