Author
Ming-Yang Kao
Other affiliations: Tufts University, Indiana University, University of North Carolina at Greensboro ...read more
Bio: Ming-Yang Kao is an academic researcher from Northwestern University. The author has contributed to research in topics: Time complexity & Planar graph. The author has an hindex of 37, co-authored 202 publications receiving 4438 citations. Previous affiliations of Ming-Yang Kao include Tufts University & Indiana University.
Papers published on a yearly basis
Papers
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16 Apr 2013
TL;DR: This paper presents an efficient algorithm for finding the optimal k-cuts of a nondecreasing array of size n that produces the maximum area under the points and believes that an O(kn) time algorithm exists and shows a heuristic algorithm.
Abstract: This paper presents an efficient algorithm for finding the optimal k-cuts of a nondecreasing array of size n that produces the maximum area under the points. The naive approach uses a dynamic programming algorithm which requires O(kn2) time, where n is the size of the array. This algorithm is time consuming for large n or k and thus inappropriate. We design faster algorithms by discovering and proving some nice properties of the nondecreasing arrays, finding convex hull, and by continuous-to-discrete transformation. We believe that an O(kn) time algorithm exists and show a heuristic algorithm.
01 May 2000
TL;DR: This work initiates research into the problem of determining an optimal investment strategy for investors with different attitudes towards the trade-offs of risk and profit.
Abstract: This work initiates research into the problem of determining an optimal investment strategy for investors with different attitudes towards the trade-offs of risk and profit. The probability distribution of the return values of the stocks that are considered by the investor are assumed to Research supported in part by NSF grants CCR-9531028 and CCR-9974871. Current address: Department of Computer Science, Northwestern University, Evanston, IL 60201, USA. Research supported in part by Texas Advanced Research Program Grant 1997-003594-019.
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01 Jan 2007
TL;DR: Contributed Papers To AAIM 2007.: Solving Generalized Maximum Dispersion with Linear Programming, Significance-Driven Graph Clustering, Improved Approximation Algorithm for Maximum Edge 2-Coloring in Simple Graphs, and more.
Abstract: Contributed Papers To AAIM 2007.- Solving Generalized Maximum Dispersion with Linear Programming.- Significance-Driven Graph Clustering.- An Improved Approximation Algorithm for Maximum Edge 2-Coloring in Simple Graphs.- Digraph Strong Searching: Monotonicity and Complexity.- Algorithms for Counting 2-Sat Solutions and Colorings with Applications.- Collaborative Ranking: An Aggregation Algorithm for Individuals' Preference Estimation.- A Compact Encoding of Rectangular Drawings with Efficient Query Supports.- A New Efficient Algorithm for Computing the Longest Common Subsequence.- Scheduling a Flexible Batching Machine.- Global Search Method for Parallel Machine Scheduling.- Releasing and Scheduling of Lots in a Wafer Fab.- Mixed Criteria Packet Scheduling.- Efficient Algorithms for k-Disjoint Paths Problems on DAGs.- Acyclic Edge Colouring of Outerplanar Graphs.- Smallest Bipartite Bridge-Connectivity Augmentation (Extended Abstract).- Approximation Algorithms for the Graph Orientation Minimizing the Maximum Weighted Outdegree.- An Efficient Algorithm for the Evacuation Problem in a Certain Class of a Network with Uniform Path-Lengths.- Online OVSF Code Assignment with Resource Augmentation.- Optimal Joint Rate and Power Allocation in CDMA Networks.- Suppressing Maximum Burst Size Throughout the Path with Non-work Conserving Schedulers.- How to Play the Majority Game with Liars.- On Satisfiability Games and the Power of Congestion Games.- The Complexity of Algorithms Computing Game Trees on Random Assignments.- An Efficient, and Fast Convergent Algorithm for Barrier Options.- An Ingenious, Piecewise Linear Interpolation Algorithm for Pricing Arithmetic Average Options.- Optimal Order Allocation with Discount Pricing.- Convex Hulls of Point-Sets and Non-uniform Hypergraphs.- Optimal st-Orientations for Plane Triangulations.- Minimum Spanning Tree with Neighborhoods.- An Almost Linear Time 2.8334-Approximation Algorithm for the Disc Covering Problem.- Optimal Field Splitting with Feathering in Intensity-Modulated Radiation Therapy.- Approximating the Maximum Independent Set and Minimum Vertex Coloring on Box Graphs.- BMA *: An Efficient Algorithm for the One-to-Some Shortest Path Problem on Road Maps.- Strip Packing vs. Bin Packing.- Probe Matrix Problems: Totally Balanced Matrices.- Efficiency of Data Distribution in BitTorrent-Like Systems.- Design of a Fuzzy PI Controller to Guarantee Proportional Delay Differentiation on Web Servers.- Improved Approximation Algorithms for Predicting RNA Secondary Structures with Arbitrary Pseudoknots.- A Heuristic Method for Selecting Support Features from Large Datasets.- Invited Lecture.- Game and Market Equilibria: Computation, Approximation, and Smoothed Analysis.- Ad Auctions - Current and Future Research.- Expressive Commerce and Its Application to Sourcing: How We Conducted $25 Billion of Generalized Combinatorial Auctions.
Posted Content•
TL;DR: In this article, a new decomposition theorem for maximum weight bipartite matchings was presented and used to design an O(sqrt(n)W/k(n,W/N))-time algorithm for computing a maximum weight matching.
Abstract: Let G be a bipartite graph with positive integer weights on the edges and without isolated nodes. Let n, N and W be the node count, the largest edge weight and the total weight of G. Let k(x,y) be log(x)/log(x^2/y). We present a new decomposition theorem for maximum weight bipartite matchings and use it to design an O(sqrt(n)W/k(n,W/N))-time algorithm for computing a maximum weight matching of G. This algorithm bridges a long-standing gap between the best known time complexity of computing a maximum weight matching and that of computing a maximum cardinality matching. Given G and a maximum weight matching of G, we can further compute the weight of a maximum weight matching of G-{u} for all nodes u in O(W) time.
TL;DR: Three efficient techniques to verify the code words, namely, the Enumeration, Table Lookup, and Encoding methods, with applications to the design of DNA words are provided.
Abstract: This paper investigates the problem of testing whether a set of code words satisfies certain biologically motivated Hamming distance constraints The paper provides three efficient techniques to verify the code words, namely, the Enumeration, Table Lookup, and Encoding methods, with applications to the design of DNA words The Enumeration method enumerates all combinations of positions in a word, so that all the words in a set can be compared simultaneously and the testing process is improved The Table Lookup method constructs a data table and divide each word into sub-words to reduce the time complexity of the testing process The Encoding method which is similar to Table Lookup method uses a linked list to store necessary information in addition The proposed methods run in O(n) ~ O(log log n) times faster than the naive method when e=O(log n), where n is the number of code words in a set and e is the length of a word
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3,734 citations
1,388 citations
TL;DR: This work experimentally demonstrated several digital logic circuits, culminating in a four-bit square-root circuit that comprises 130 DNA strands, which enables fast and reliable function in large circuits with roughly constant switching time and linear signal propagation delays.
Abstract: To construct sophisticated biochemical circuits from scratch, one needs to understand how simple the building blocks can be and how robustly such circuits can scale up. Using a simple DNA reaction mechanism based on a reversible strand displacement process, we experimentally demonstrated several digital logic circuits, culminating in a four-bit square-root circuit that comprises 130 DNA strands. These multilayer circuits include thresholding and catalysis within every logical operation to perform digital signal restoration, which enables fast and reliable function in large circuits with roughly constant switching time and linear signal propagation delays. The design naturally incorporates other crucial elements for large-scale circuitry, such as general debugging tools, parallel circuit preparation, and an abstraction hierarchy supported by an automated circuit compiler.
1,249 citations
TL;DR: A new de novo sequencing software package, PEAKS, is described, to extract amino acid sequence information without the use of databases, using a new model and a new algorithm to efficiently compute the best peptide sequences whose fragment ions can best interpret the peaks in the MS/MS spectrum.
Abstract: A number of different approaches have been described to identify proteins from tandem mass spectrometry (MS/MS) data. The most common approaches rely on the available databases to match experimental MS/MS data. These methods suffer from several drawbacks and cannot be used for the identification of proteins from unknown genomes. In this communication, we describe a new de novo sequencing software package, PEAKS, to extract amino acid sequence information without the use of databases. PEAKS uses a new model and a new algorithm to efficiently compute the best peptide sequences whose fragment ions can best interpret the peaks in the MS/MS spectrum. The output of the software gives amino acid sequences with confidence scores for the entire sequences, as well as an additional novel positional scoring scheme for portions of the sequences. The performance of PEAKS is compared with Lutefisk, a well-known de novo sequencing software, using quadrupole-time-of-flight (Q-TOF) data obtained for several tryptic peptides from standard proteins.
1,239 citations
TL;DR: It is suggested that DNA strand displacement cascades could be used to endow autonomous chemical systems with the capability of recognizing patterns of molecular events, making decisions and responding to the environment.
Abstract: The impressive capabilities of the mammalian brain—ranging from perception, pattern recognition and memory formation to decision making and motor activity control—have inspired their re-creation in a wide range of artificial intelligence systems for applications such as face recognition, anomaly detection, medical diagnosis and robotic vehicle control Yet before neuron-based brains evolved, complex biomolecular circuits provided individual cells with the ‘intelligent’ behaviour required for survival However, the study of how molecules can ‘think’ has not produced an equal variety of computational models and applications of artificial chemical systems Although biomolecular systems have been hypothesized to carry out neural-network-like computations in vivo and the synthesis of artificial chemical analogues has been proposed theoretically, experimental work has so far fallen short of fully implementing even a single neuron Here, building on the richness of DNA computing and strand displacement circuitry, we show how molecular systems can exhibit autonomous brain-like behaviours Using a simple DNA gate architecture that allows experimental scale-up of multilayer digital circuits, we systematically transform arbitrary linear threshold circuits (an artificial neural network model) into DNA strand displacement cascades that function as small neural networks Our approach even allows us to implement a Hopfield associative memory with four fully connected artificial neurons that, after training in silico, remembers four single-stranded DNA patterns and recalls the most similar one when presented with an incomplete pattern Our results suggest that DNA strand displacement cascades could be used to endow autonomous chemical systems with the capability of recognizing patterns of molecular events, making decisions and responding to the environment
884 citations