ppxscal/embedding_network huggingface dataset:
Law discovery using neural networks
Authors: Kazumi Saito, Ryohei Nakano
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

This paper proposes a new connectionist approach to numeric law discovery; i.e., neural networks (law-candidates) are trained by using a newly invented second-order learning algor ithm based on a quasi-Newton method, called BPQ, and the Minimum Description Length criterion selects the most suitable from lawcandidates. The main advantage of our method over previous work of symbolic or connectionist approach is that it can efficiently discover numeric laws whose power values are not restricted to integers. Experiments showed that the proposed method works well in discovering such laws even from data containing irrelevant variables or a small amount of noise.
A Machine Learning Approach to Off-Line Signature Verification Using Bayesian Inference
Authors: Danjun Pu, Gregory R. Ball, Sargur N. Srihari
Venue: Proceedings of the 3rd International Workshop on Computational Forensics (2009)

A machine learning approach to off-line signature verification is presented. The prior distributions are determined from genuine and forged signatures of several individuals. The task of signature verification is a problem of determining genuine-class membership of a questioned (test) signature. We take a 3-step, writer independent approach: 1) Determine the prior parameter distributions for means of both "genuine vs. genuine" and "forgery vs. known" classes using a distance metric. 2) Enroll n genuine and m forgery signatures for a particular writer and calculate both the posterior class probabilities for both classes. 3) When evaluating a questioned signature, determine the probabilities for each class and choose the class with bigger probability. By using this approach, performance over other approaches to the same problem is dramatically improved, especially when the number of available signatures for enrollment is small. On the NISDCC dataset, when enrolling 4 genuine signatures, the new method yielded a 12.1% average error rate, a significant improvement over a previously described Bayesian method.
Minimum Disclosure Counting for the Alternative Vote
Authors: Roland Wen, Richard Buckland
Venue: Proceedings of the 2nd International Conference on E-Voting and Identity (2009)

Although there is a substantial body of work on preventing bribery and coercion of voters in cryptographic election schemes for plurality electoral systems, there are few attempts to construct such schemes for preferential electoral systems. The problem is preferential systems are prone to bribery and coercion via subtle signature attacks during the counting. We introduce a minimum disclosure counting scheme for the alternative vote preferential system. Minimum disclosure provides protection from signature attacks by revealing only the winning candidate.
The bipanpositionable bipancyclic property of the hypercube
Authors: Yuan-Kang Shih, Cheng-Kuan Lin, Jimmy J. M. Tan, Lih-Hsing Hsu
Venue: Computers Mathematics with Applications (2009)

A bipartite graph is bipancyclic if it contains a cycle of every even length from 4 to |V(G)| inclusive. A hamiltonian bipartite graph G is bipanpositionable if, for any two different vertices x and y, there exists a hamiltonian cycle C of G such that d"C(x,y)=k for any integer k with d"G(x,y)@?k@?|V(G)|/2 and (k-d"G(x,y)) being even. A bipartite graph G is k-cycle bipanpositionable if, for any two different vertices x and y, there exists a cycle of G with d"C(x,y)=l and |V(C)|=k for any integer l with d"G(x,y)@?l@?k2 and (l-d"G(x,y)) being even. A bipartite graph G is bipanpositionable bipancyclic if G is k-cycle bipanpositionable for every even integer k, 4@?k@?|V(G)|. We prove that the hypercube Q"n is bipanpositionable bipancyclic for n>=2.
A Strong Law of Large Numbers for Markov Chain Fields on a Special Non-homogeneous Tree
Authors: Jin Shaohua, Zhong Yanyan, Wan Yanping, Chen Xiuyin
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

The strong laws oflarge numbers is one of the central questions for studying in the international Probability theory. In this paper, a stronglaw of large numbers for Markov chain fields on a Special Non-homogeneous tree is given by constructing a non-negative martingale and usingDoob’smartingale convergence theorem.
Dormant independence
Authors: Ilya Shpitser, Judea Pearl
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 2 (2008)

The construction of causal graphs from nonexperimental data rests on a set of constraints that the graph structure imposes on all probability distributions compatible with the graph. These constraints are of two types: conditional independencies and algebraic constraints, first noted by Verma. While conditional independencies are well studied and frequently used in causal induction algorithms, Verma constraints are still poorly understood, and rarely applied. In this paper we examine a special subset of Verma constraints which are easy to understand, easy to identify and easy to apply; they arise from "dormant independencies," namely, conditional independencies that hold in interventional distributions. We give a complete algorithm for determining if a dormant independence between two sets of variables is entailed by the causal graph, such that this independence is identifiable, in other words if it resides in an interventional distribution that can be predicted without resorting to interventions. We further show the usefulness of dormant independencies in model testing and induction by giving an algorithm that uses constraints entailed by dormant independencies to prune extraneous edges from a given causal graph.
MELB-YB: preposition sense disambiguation using rich semantic features
Authors: Patrick Ye, Timothy Baldwin
Venue: Proceedings of the 4th International Workshop on Semantic Evaluations (2007)

This paper describes a maxent-based preposition sense disambiguation system entry to the preposition sense disambiguation task of the SemEval 2007. This system uses a wide variety of semantic and syntactic features to perform the disambiguation task and achieves a precision of 69.3% over the test data.
Adaptive video-on-demand broadcasting in ubiquitous computing environment
Authors: Chao Peng, Yasuo Tan, Naixue Xiong, Laurence T. Yang, Jong Hyuk Park, Soon-Seok Kim
Venue: Personal and Ubiquitous Computing (2009)

Video-on-demand (VOD) is a service that allows users to view any video program from a server at the time of their choice, such kind of services are expected to be popular in future ubiquitous computing environment. Lots of broadcasting protocols for VOD services have been proposed, but they usually focus only on the tradeoff between bandwidth and delay, thus they are usually not efficient for the local storage. Since the ubiquitous network is heterogeneous and users will have different resource and communication capability, we need to address the storage issue in VOD systems. In this paper, we present several new effective broadcasting schemes, which can intelligently adjust the solution according to available bandwidth and local storage to achieve an ideal waiting time.
Filtering, decomposition and search space reduction for optimal sequential planning
Authors: Stéphane Grandcolas, Cyril Pain-Barre
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

We present in this paper a hybrid planning system Which combines constraint satisfaction techniques and planning heuristics to produce optimal sequential plans. It integrates its own consistency rules and filtering and decomposition mechanisms suitable for planning. Given a fixed bound on the plan length, our planner works directly on a structure related to Graphplan's planning graph. This structure is incrementally built: Each time it is extended, a sequential plan is searched. Different search strategies may be employed. Currently, it is a forward chaining search based on problem decomposition with action sets partitioning. Various techniques are used to reduce the search space, such as memorizing nogood states or estimating goals reachability. In addition, the planner implements two different techniques to avoid enumerating some equivalent action sequences. Empirical evaluation shows that our system is very competitive on many problems, especially compared to other optimal sequential planners.
Deep linguistic processing for spoken dialogue systems
Authors: James Allen, Mehdi Manshadi, Myroslava Dzikovska, Mary Swift
Venue: Proceedings of the Workshop on Deep Linguistic Processing (2007)

We describe a framework for deep linguistic processing for natural language understanding in task-oriented spoken dialogue systems. The goal is to create domaingeneral processing techniques that can be shared across all domains and dialogue tasks, combined with domain-specific optimization based on an ontology mapping from the generic LF to the application ontology. This framework has been tested in six domains that involve tasks such as interactive planning, coordination operations, tutoring, and learning.
Urban Innovation Based on the Environmental Management
Authors: Yang Tong, Wang Nengmin
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

Environmental management are collection ofenvironmental standards, green technological innovation related to patent protection system, economic instruments, financial instruments, and other measures to limit damage to the environmental quality of human. This issue Analysis environmental management mechanisms from the economics perspective: Additional new targets affect the uncertainty of environment in the process of technological innovation, thus to make the goal of innovation more clearly. At the same time, it induces the cities’ independent innovation of enterprises, urban management innovation and government policy innovation. It points out that towns only face the new competition structure pro-actively, and make full use of new environmental technology and management methods can it create their own competitive advantage.
Are We There Yet? Research in Commercial Spoken Dialog Systems
Authors: Roberto Pieraccini, David Suendermann, Krishna Dayanidhi, Jackson Liscombe
Venue: Proceedings of the 12th International Conference on Text, Speech and Dialogue (2009)

In this paper we discuss the recent evolution of spoken dialog systems in commercial deployments. Yet based on a simple finite state machine design paradigm, dialog systems reached today a higher level of complexity. The availability of massive amounts of data during deployment led to the development of continuous optimization strategy pushing the design and development of spoken dialog applications from an art to science. At the same time new methods for evaluating the subjective caller experience are available. Finally we describe the inevitable evolution for spoken dialog applications from speech only to multimodal interaction.
From handheld collaborative tool to effective classroom module: embedding CSCL in a broader design framework
Authors: Jeremy Roschelle, Ken Rafanan, Gucci Estrella, Miguel Nussbaum, Susana Claro
Venue: Proceedings of the 9th international conference on Computer supported collaborative learning - Volume 1 (2009)

The TechPALS project expanded a general-purpose handheld CSCL tool (from Chile) to a 3-week classroom module for primary school mathematics (in the United States). To go from tool to module we articulated a framework for an effective CSCL practice-including curricular fit, training materials, pedagogical guidance, formative and summative assessments, and logistical support. In parallel, to meet requirements of the U.S. Department of Education, we conducted classroom experiments to investigate the achievement differences between students who were randomized to use either TechPALS or a non-CSCL product. In this paper, we examine the design changes from initial classroom pilot tests to eventual attainment of statistically significant results, emphasizing the integration of technology, activity designs, and broader educational practices that was required to achieve impacts in ordinary, low-income schools. Based on these results, we recommend a "curricular activity system" framework to support effective CSCL practices.
Priority Assignment Under Imperfect Information on Customer Type Identities
Authors: Nilay Tanık Argon, Serhan Ziya
Venue: Manufacturing Service Operations Management (2009)

In many service systems, customers are not served in the order they arrive, but according to a priority scheme that ranks them with respect to their relative “importance.” However, it may not be an easy task to determine the importance level of customers, especially when decisions need to be made under limited information. A typical example is from health care: When triage nurses classify patients into different priority groups, they must promptly determine each patient's criticality levels with only partial information on their conditions. We consider such a service system where customers are from one of two possible types. The service time and waiting cost for a customer depends on the customer's type. Customers' type identities are not directly available to the service provider; however, each customer provides a signal, which is an imperfect indicator of the customer's identity. The service provider uses these signals to determine priority levels for the customers with the objective of minimizing the long-run average waiting cost. In most of the paper, each customer's signal equals the probability that the customer belongs to the type that should have a higher priority and customers incur waiting costs that are linear in time. We first show that increasing the number of priority classes decreases costs, and the policy that gives the highest priority to the customer with the highest signal outperforms any finite class priority policy. We then focus on two-class priority policies and investigate how the optimal policy changes with the system load. We also investigate the properties of “good” signals and find that signals that are larger in convex ordering are more preferable. In a simulation study, we find that when the waiting cost functions are nondecreasing, quadratic, and convex, the policy that assigns the highest priority to the customer with the highest signal performs poorly while the two-class priority policy and an extension of the generalized cμ rule perform well.
The Impact of Different Embodied Agent-Feedback on Users' Behavior
Authors: Astrid Pütten, Christian Reipen, Antje Wiedmann, Stefan Kopp, Nicole C. Krämer
Venue: Proceedings of the 9th International Conference on Intelligent Virtual Agents (2009)

This study investigated whether emotional expressions of an ECA influence the participants' nonverbal and verbal behavior. 70 participants took part in a small talk (10 min.) situation with the ECA MAX who was presented with two different types of feedback: emotional feedback (EMO), which provided a feedback about the emotional state of MAX (including smiles and compliments) and envelope feedback (ENV), which provided a feedback about the comprehension of the participants' contributions. In general we found that participants showed frequent behavior known from human-human-communication, such as proactive greetings or waving goodbye. Additionally, with regard to some behaviors, the agent's behavior had an impact: Participants in EMO significantly gave more compliments and exhibited more phrases of politeness ("Thank you!") than in ENV.
Do not forget: full memory in memory-based learning of word pronunciation
Authors: Antal van den Bosch, Walter Daelemans
Venue: Proceedings of the Joint Conferences on New Methods in Language Processing and Computational Natural Language Learning (1998)

Memory-based learning, keeping full memory of learning material, appears a viable approach to learning NLP tasks, and is often superior in generalisation accuracy to eager learning approaches that abstract from learning material. Here we investigate three partial memory-based learning approaches which remove from memory specific task instance types estimated to be exceptional. The three approaches each implement one heuristic function for estimating exceptionality of instance types: (i) typicality, (ii) class prediction strength, and (iii) friendly-neighbourhood size. Experiments are performed with the memory-based learning algorithm IB1-IG trained on English word pronunciation. We find that removing instance types with low prediction strength (ii) is the only tested method which does not seriously harm generalisation accuracy. We conclude that keeping full memory of types rather than tokens, and excluding minority ambiguities appear to be the only performance-preserving optimisations of memory-based learning.
Resource Allocation in MIMO-OFDMA Wireless Systems Based on Linearly Precoded Orthogonal Space-Time Block Codes
Authors: Borja Dañobeitia, Guillem Femenias, Felip Riera-Palou
Venue: Proceedings of the 15th Open European Summer School and IFIP TC6.6 Workshop on The Internet of the Future (2009)

This paper proposes and analyzes efficient rate and power allocation algorithms for MIMO-OFDMA broadcast channels based on linearly precoded orthogonal space-time block codes. The weighted sum-rate maximization problem is considered for both continuous and discrete rate allocation schemes. Since this problem is non-convex and combinatorial in nature, the Lagrange dual decomposition method is used to find an accurate near-optimal solution. The effects of using different MIMO configurations and realistic channel models with space and frequency correlation over the weighted sum-rate of the system is considered.
Generalized evidence pre-propagated importance sampling for hybrid Bayesian networks
Authors: Changhe Yuan, Marek J. Druzdzel
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

In this paper, we first provide a new theoretical understanding of the Evidence Pre-propagated Importance Sampling algorithm (EPIS-BN) (Yuan & Druzdzel 2003; 2006b) and show that its importance function minimizes the KL-divergence between the function itself and the exact posterior probability distribution in Polytrees. We then generalize the method to deal with inference in general hybrid Bayesian networks consisting of deterministic equations and arbitrary probability distributions. Using a novel technique called soft arc reversal, the new algorithm can also handle evidential reasoning with observed deterministic variables.
Efficient and secure protocols for privacy-preserving set operations
Authors: Yingpeng Sang, Hong Shen
Venue: ACM Transactions on Information and System Security (TISSEC) (2009)

Many applications require performing set operations without publishing individual datesets. In this article, we address this problem for five fundamental set operations including set intersection, cardinality of set intersection, element reduction, overthreshold set-union, and subset relation. Our protocols are obtained in the universally composable security framework, in the assumption of the probabilistic polynomial time bounded adversary, which actively controls a fixed set of t parties and the assumption of an authenticated broadcast channel. Our constructions utilize building blocks of nonmalleable NonInteractive Zero-Knowledge (NIZK) arguments, which are based on a (t + 1,N)-threshold version (N is the number of parties in the protocol) of the boneh-goh-nissim (BGN) cryptosystem whose underlying group supports bilinear maps, in the assumption that the public key and shares of the secret key have been generated by a trusted dealer. The previous studies were all based on the stand-alone model with the same assumptions on the adversary, broadcast channel, and key generation. For the first four operations, we propose protocols that improve the previously known results by an O(N) factor in the computation and communication complexities. For the subset relation, our protocol is the first one secure against the active adversary. Our constructions of NIZK have independent interest in that, though also mentioned as building blocks, the previous work did not illustrate how to construct them. We construct these NIZK with an additional nonmalleable property, the same complexity as claimed in the previous work, and also an improvement on the communication complexity.
Characterisation of Liquid Properties by Electrical Capacitance Tomography Sensor for Security Applications
Authors: Nan Li, Bao-long Guo, Chuan Huang
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01 (2009)

The ECT sensor based on electrical permittivity measurements is presented which may be applied to security application for contactless detection of flammable and explosive liquid. The structure, geometry and size of ECT sensor are discussed in this paper; two types of capacitance sensor are designed and compared. COMSOL simulation software is used to evaluate the performance of designed sensor. An impedance analyzer is used to measure the capacitance between each electrode pair. Results analysis is provided, the feasibility of ECT sensor using in liquid testing for security application is proved at the conclusion part.
Increasing the Efficiency of Next-Generation Space Operations by Exploiting Predictability
Authors: Daniel Fischer, Knut Eckstein, David Basin, Thomas Engel
Venue: Proceedings of the Third IEEE International Conference on Space Mission Challenges for Information Technology (2009)

From a mobile networking perspective, spacecraft networks are characterized by the predictability of node movement and communication opportunities. We show that payload data throughput, spacecraft commanding, and mission autonomy can be enhanced by using a predicable mobile routing protocol. We validate our claims through realistic network simulations in the context of a complex communication infrastructure for a next-generation Mars mission. Moreover, we propose routing protocol enhancements that also takes intermittently connected links into account as they occur in delay-tolerant networking. Finally, we analyze the operational impact and capabilities of the routing protocol on spacecraft commanding and operations.
Audio Steganalysis Based on Co-occurrence Matrix and PCA
Authors: Yinchen Qi, Yan Wang, Jinsha Yuan
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

A new steganalysis scheme based on co-occurrence matrix for audio signals is proposed. The statistics features are derived from the co-occurrence matrix firstly, which are calculated from amplitude of audio signals. Then the preprocessing of principal component analysis (PCA) is used on statistics features and the support vector machine (SVM) is used as a classifier. Experiment results for 450 audio signals of CASIA98-99 audio database show that the detection rates of three audio data hidden methods (wavelet domain least significant bit, quantization index method and addition method) are all greater than 92%.
Logarithmic order and type of indeterminate moment problems II
Authors: Henrik L. Pedersen
Venue: Journal of Computational and Applied Mathematics (2009)

We show that there exist indeterminate Stieltjes moment problems with prescribed common logarithmic order and type.