33412733
Learning a Hidden Graph Using O(log n) Queries Per Edge
We consider the problem of learning a general graph using edge-detecting queries. In this model, the learner may query whether a set of vertices induces an edge of the hidden graph. This model has been studied for particular classes of graphs by Kucherov and Grebinski [1] and Alon et al.[2], motivated by problems arising in genome sequencing. We give an adaptive deterministic algorithm that learns a general graph with n vertices and m edges using O(m log n) queries, which is tight up to a constant factor for classes of non-dense graphs. Allowing randomness, we give a 5-round Las Vegas algorithm using \(O(m {\rm log}n+\sqrt{m}{\rm log}^{2}n)\) queries in expectation. We give a lower bound of Ω((2m/r) r/2) for learning the class of non-uniform hypergraphs of dimension r with m edges. For the class of r-uniform hypergraphs with bounded degree d, where d≤ n 1/( r− − 1)/(2r 1 + 2/( r− − 1)), we give a non-adaptive Monte Carlo algorithm using O(dnlog n) queries, which succeeds with probability at least 1–n − − c, where c is any constant.
5765721
Architecture of TsinghuAeolus
RoboCup Simulation Server provides a wonderful challenge for all the participants. This paper explains key technology implemented by Tsinghuaeolus RoboCup team played in RoboCup environment, including basic adversarial skills, which is developed by using Dynamic Programming in combination with heuristic search algorithm, and reactive strategy architecture. Tsinghuaeolus was the winner of RoboCup2001.
3103973
Sprite: a simple, cheat-proof, credit-based system for mobile ad-hoc networks
Mobile ad hoc networking has been an active research area for several years. How to stimulate cooperation among selfish mobile nodes, however, is not well addressed yet. In this paper, we propose Sprite, a simple, cheat-proof, credit-based system for stimulating cooperation among selfish nodes in mobile ad hoc networks. Our system provides incentive for mobile nodes to cooperate and report actions honestly. Compared with previous approaches, our system does not require any tamper-proof hardware at any node. Furthermore, we present a formal model of our system and prove its properties. Evaluations of a prototype implementation show that the overhead of our system is small. Simulations and analysis show that mobile nodes can cooperate and forward each other's messages, unless the resource of each node is extremely low.
33317527
Learning Large-Alphabet and Analog Circuits with Value Injection Queries
We consider the problem of learning an acyclic discrete circuit with n wires, fan-in bounded by k and alphabet size s using value injection queries. For the class of transitively reduced circuits, we develop the Distinguishing Paths Algorithm, that learns such a circuit using (ns)O(k) value injection queries and time polynomial in the number of queries. We describe a generalization of the algorithm to the class of circuits with shortcut width bounded by b that uses (ns)O(k+b) value injection queries. Both algorithms use value injection queries that fix only O(kd) wires, where d is the depth of the target circuit. We give a reduction showing that without such restrictions on the topology of the circuit, the learning problem may be computationally intractable when s = nΘ(1), even for circuits of depth O(log n). We then apply our large-alphabet learning algorithms to the problem of approximate learning of analog circuits whose gate functions satisfy a Lipschitz condition. Finally, we consider models in which behavioral equivalence queries are also available, and extend and improve the learning algorithms of [5] to handle general classes of gates functions that are polynomial time learnable from counterexamples.
628849
Learning a circuit by injecting values
We propose a new model for exact learning of acyclic circuits using experiments in which chosen values may be assigned to an arbitrary subset of wires internal to the circuit, but only the value of the circuit's single output wire may be observed. We give polynomial time algorithms to learn (1) arbitrary circuits with logarithmic depth and constant fan-in and (2) Boolean circuits of constant depth and unbounded fan-in over AND, OR, and NOT gates. Thus, both AC0 and NC1 circuits are learnable in polynomial time in this model. Negative results show that some restrictions on depth, fan-in and gate types are necessary: exponentially many experiments are required to learn AND/OR circuits of unbounded depth and fan-in; it is NP-hard to learn AND/OR circuits of unbounded depth and fan-in 2; and it is NP-hard to learn circuits of bounded depth and unbounded fan-in over AND, OR, and threshold gates, even when the target circuit is known to contain at most one threshold gate and that threshold gate has threshold 2. We also consider the effect of adding an oracle for behavioral equivalence. In this case there are polynomial-time algorithms to learn arbitrary circuits of constant fan-in and unbounded depth and to learn Boolean circuits with arbitrary fan-in and unbounded depth over AND, OR, and NOT gates. A corollary is that these two classes are PAC-learnable if experiments are available.
16222163
Learning a Hidden Hypergraph
We consider the problem of learning a hypergraph using edge-detecting queries. In this model, the learner may query whether a set of vertices induces an edge of the hidden hypergraph or not. We show that an r-uniform hypergraph with m edges and n vertices is learnable with O(2 4r m.poly(r,logn)) queries with high probability. The queries can be made in O(min(2 r r 2 log 2 n, r 3 log 3 n)) rounds. We also give an algorithm that learns a non-uniform hypergraph whose minimum edge size is r 1 and maximum edge size is r 2 using O(f 1 (r 1 ,r 2 ).m (r 2 -r 1 +2)/2 . poly(log n)) queries with high probability, and give a lower bound of Ω(f 2 (r 1 ,r 2 ).m (r 2 -r 1 +2)/2 for this class of hypergraphs, where fi and f 2 are functions depending only on r 1 and r 2 . The queries can also be made in O(min(2 r 2r 2 2 log 2 n, r 3 2 log 3 n)) rounds.
18640612
On approximating minimum vertex cover for graphs with perfect matching
It has been a challenging open problem whether there is a polynomial time approximation algorithm for the VERTEX COVER problem whose approximation ratio is bounded by a constant less than 2. In this paper, we study the VERTEX COVER problem on graphs with perfect matching (shortly, VC-PM). We show that if the VC-PM problem has a polynomial time approximation algorithm with approximation ratio bounded by a constant less than 2, then so does the VERTEX COVER problem on general graphs. Approximation algorithms for VC-PM are developed, which induce improvements over previously known algorithms on sparse graphs. For example, for graphs of average degree 5, the approximation ratio of our algorithm is 1.414, compared with the previously best ratio 1.615 by Halldorsson and Radhakrishnan.
9144862
Rules and fuzzy rules in text: concept, extraction and usage
Several concepts and techniques have been imported from other disciplines such as Machine Learning and Artificial Intelligence to the field of textual data. In this paper, we focus on the concept of rule and the management of uncertainty in text applications. The different structures considered for the construction of the rules, the extraction of the knowledge base and the applications and usage of these rules are detailed. We include a review of the most relevant works of the different types of rules based on their representation and their application to most of the common tasks of Information Retrieval such as categorization, indexing and classification.
30612222
Constrained minimum vertex cover in bipartite graphs: complexity and parameterized algorithms
Motivated by the research in reconfigurable memory array structures, this paper studies the complexity and algorithms for the constrained minimum vertex cover problem on bipartite graphs (NIN-CVCB) defined as follows: given a bipartite graph G = (V, E) with vertex bipartition V = U ∪ L and two integers ku and kl, decide whether there is a minimum vertex cover in G with at most ku vertices in U and at most kl vertices in L. It is proved in this paper that the MIN-CVCB problem is NP-complete. This answers a question posed by Hasan and Liu. A parameterized algorithm is developed for the problem, in which classical results in matching theory and recently developed techniques in parameterized computation theory are nicely combined and extended. The algorithm runs in time O(1.26ku + kl + (ku + kl) |G|) and significantly improves previous algorithms for the problem.
1373438
On Approximating Minimum Vertex Cover for Graphs with Perfect Matching
It has been a challenging open problem whether there is a polynomial time approximation algorithm for the VERTEX COVER problem whose approximation ratio is bounded by a constant less than 2. In this paper, we study the VERTEX COVER problem on graphs with perfect matching (shortly, VC-PM). We show that if the VC-PM problem has a polynomial time approximation algorithm with approximation ratio bounded by a constant less than 2, then so does the VERTEX COVER problem on general graphs. Approximation algorithms for VC-PM are developed, which induce improvements over previously known algorithms on sparse graphs. For example, for graphs of average degree 5, the approximation ratio of our algorithm is 1.414, compared with the previously best ratio 1.615 by Halldorsson and Radhakrishnan.
193728
Feedback-based Scheduling for Back-end Databases in Shared Dynamic Content Server Clusters
This paper introduces a self-configuring architecture for scaling the database tier of dynamic content Web servers. We use a unified approach to load and fault management based on dynamic data replication and feedback-based scheduling. While replication provides scaling and high availability, feedback scheduling dynamically allocates tasks to commodity databases across workloads in response to peak loads or failure conditions thus providing quality of service. By augmenting the feedback loop with state awareness, we avoid oscillations in resource allocation. We investigate our transparent provisioning mechanisms in the database tier using the TPC-W e-commerce and the on-line auction Rubis benchmarks. We demonstrate that our techniques provide quality of service under load bursts and failure scenarios