ppxscal/embedding_network huggingface dataset:
Progress in the AMIDA Speaker Diarization System for Meeting Data
Authors: David A. Leeuwen, Matej Konečný
Venue: Multimodal Technologies for Perception of Humans: International Evaluation Workshops CLEAR 2007 and RT 2007, Baltimore, MD, USA, May 8-11, 2007, Revised Selected Papers (2008)

In this paper we describe the AMIDA speaker dizarization system as it was submitted to the NIST Rich Transcription evaluation 2007 for conference room data. This is done in the context of the history of this system and other speaker diarization systems. One of the goals of our system is to have as little tunable parameters as possible, while maintaining performance. The system consists of a BIC segmentation/clustering initialization, followed by a combined re-segmentation cluster merging algorithm. The Diarization Error Rate (DER) result of our best system is 17.0 %, accounting for overlapping speech. However, we find that a slight altering of Speech Activity Detection models has a large impact on the speaker DER.
Learning distance functions for exemplar-based object recognition
Authors: Jitendra Malik
Venue:  (2007)

This thesis investigates an exemplar-based approach to object recognition that learns, on an image-by-image basis, the relative importance of patch-based features for determining similarity. We borrow the idea of "family resemblances" from Wittgenstein's Philosophical Investigations and Eleanor Rosch's psychological studies to support the idea of learning the detailed relationships between images of the same category, which is a departure from some popular machine learning approaches such as Support Vector Machines that seek only the boundaries between categories. We represent images as sets of patch-based features. To find the distance between two images, we first find for each patch its nearest patch in the other image and compute their inter-patch distance. The weighted sum of these inter-patch distances is defined to be the distance between the two images. The main contribution of this thesis is a method for learning a set-to-set distance function specific to each training image and demonstrating the use of these functions for image browsing, retrieval, and classification. The goal of the learning algorithm is to assign a non-negative weight to each patch-based feature of the image such that the most useful patches are assigned large weights and irrelevant or confounding patches are given zero weights. We formulate this as a large-margin optimization, related to the soft-margin Support Vector Machine, and discuss two versions: a "focal" version that learns weights for each image separately, and a "global" version that jointly learns the weights for all training images. In the focal version, the distance functions learned for the training images are not directly comparable to one another and can be most directly applied to in-sample applications such as image browsing, though with heuristics or additional learning, these functions can be used for image retrieval or classification. The global approach, however, learns distance functions that are globally consistent and can be used directly for image retrieval and classification. Using geometric blur and simple color features, we show that both versions perform as well or better than the best-performing algorithms on the Caltech 101 object recognition benchmark. The global version achieves the best results, a 63.2% mean recognition rate when trained with fifteen images per category and 66.6% when trained with twenty.
A Polyhedral Model in Euclidean 3-Space of the Six-Pentagon Map of the Projective Plane
Authors: Lajos Szilassi
Venue: Discrete Computational Geometry (2008)

In a private communication, Branko Gr&#x00fc;nbaum asked: &#x201c;I wonder whether you know anything about the possibility of realizing as a polyhedron in Euclidean 3-space the family of six pentagons, that is a model of the projective plane arising by identifying antipodal points of the regular dodecahedron. Naturally, any realization must have some self-intersections&#x2014;but is there any realization that is not completely contained in a plane?&#x201d; We show that it is possible to realize this polyhedron; in our realization five of the six faces are simple polygons. In this model there are sets of three faces, which form a realization of the M&#x00f6;bius strip without self-intersections. There are four variants of the model. We conjecture that in any model of this polyhedron there must be at least one self-intersecting face.
Survey of Electrical Engineering and Computer Science Departments in the U. S.
Authors: M. E. Sloan
Venue: Computer (1975)

As a part of a major curriculum study undertaken by the IEEE Computer Society Education Committee in the fall of 1974, a subcommittee surveyed existing curriculum and equipment in both computer science and electrical engineering departments to assess the current situation. The survey was also intended to update the COSINE survey of electrical engineering departments conducted in the fall of 1972.1 The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
The Turning Points on MLP's Error Surface
Authors: Hung-Han Chen
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

This paper presents a different view on the issue of local minima and introduces a new search method for Backpropagation learning algorithm of Multi-Layer Perceptrons (MLP). As in conventional point of view, Back-propagation may be trapped at local minima instead of finding the global minimum. This concept often leads to less confidence that people may have on neural networks. However, one could argue that most of local minima may be caused by the limitation of search methods. Therefore a new search method to address this situation is proposed in this paper. This new method, "retreat and turn", has been applied to several different types of data alone or combined with other techniques. The encouraging results are included in this paper.
Static Analysis on x86 Executables for Preventing Automatic Mimicry Attacks
Authors: Danilo Bruschi, Lorenzo Cavallaro, Andrea Lanzi
Venue: Proceedings of the 4th international conference on Detection of Intrusions and Malware, and Vulnerability Assessment (2007)

In 2005, Kruegel et al. proposed a variation of the traditional mimicry attack, to which we will refer to as automatic mimicry, which can defeat existing system call based HIDS models. We show how such an attack can be defeated by using information provided by the Interprocedural Control Flow Graph (ICFG). Roughly speaking, by exploiting the ICFG of a protected binary, we propose a strategy based on the use of static analysis techniques which is able to localize critical regions inside a program, which are segments of code that could be used for exploiting an automatic mimicry attack. Once the critical regions have been recognized, their code is instrumented in such a way that, during the executions of such regions, the integrity of the dangerous code pointers is monitored, and any unauthorized modification will be restored at once with the legal values. Moreover, our experiments shows that such a defensive mechanism presents a low run-time overhead.
Sign-Solvable Linear Complementarity Problems
Authors: Naonori Kakimura
Venue: Proceedings of the 12th international conference on Integer Programming and Combinatorial Optimization (2007)

This paper presents a connection between qualitative matrix theory and linear complementarity problems (LCPs). An LCP is said to be sign-solvable if the set of the sign patterns of the solutions is uniquely determined by the sign patterns of the given coefficients. We provide a characterization for sign-solvable LCPs such that the coefficient matrix has nonzero diagonals, which can be tested in polynomial time. This characterization leads to an efficient combinatorial algorithm to find the sign pattern of a solution for these LCPs. The algorithm runs in O(¿) time, where ¿ is the number of the nonzero coefficients.
Filtering for Improving the Geographic Information Search
Authors: José M. Perea-Ortega, Miguel A. García-Cumbreras, Manuel García-Vega, L. A. Ureña-López
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

This paper describes the GEOUJA System, a Geographical Information Retrieval (GIR) system submitted by the SINAI group of the University of Jaén in GeoCLEF 2007. The objective of our system is to filter the documents retrieved from an information retrieval (IR) subsystem, given a multilingual statement describing a spatial user need. The results of the experiments show that the new heuristics and rules applied in the geo-relation validator module improve the general precision of our system. The increasing of the number of documents retrieved by the information retrieval subsystem also improves the final results.
Improved search engines and navigation preference in personal information management
Authors: Ofer Bergman, Ruth Beyth-Marom, Rafi Nachmias, Noa Gradovitch, Steve Whittaker
Venue: ACM Transactions on Information Systems (TOIS) (2008)

Traditionally users access their personal files mainly by using folder navigation. We evaluate whether recent improvements in desktop search have changed this fundamental aspect of Personal Information Management (PIM). We tested this in two studies using the same questionnaire: (a) The Windows Studya longitudinal comparison of Google Desktop and Windows XP Search Companion, and (b) The Mac Studya large scale comparison of Mac Spotlight and Sherlock. There were few effects for improved search. First, regardless of search engine, there was a strong navigation preference: on average, users estimated that they used navigation for 56-68% of file retrieval events but searched for only 4-15% of events. Second, the effect of improving the quality of the search engine on search usage was limited and inconsistent. Third, search was used mainly as a last resort when users could not remember file location. Finally, there was no evidence that using improved desktop search engines leads people to change their filing habits to become less reliant on hierarchical file organization. We conclude by offering theoretical explanations for navigation preference, relating to differences between PIM and Internet retrieval, and suggest alternative design directions for PIM systems.
Managing Groups of Files in a Rule Oriented Data Management System (iRODS)
Authors: Andrea Weise, Mike Wan, Wayne Schroeder, Adil Hasan
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

The iRODS system, created by the San Diego Supercomputing Centre, is a rule oriented data management system that allows the user to create sets of rules to define how the data is to be managed. Each rule corresponds to a particular action or operation (such as checksumming a file) and the system is flexible enough to allow the user to create new rules for new types of operations. The iRODS system can interface to any storage system (provided an iRODS driver is built for that system) and relies on its' metadata catalogue to provide a virtual file-system that can handle files of any size and type.However, some storage systems (such as tape systems) do not handle small files efficiently and prefer small files to be packaged up (or "bundled") into larger units. We have developed a system that can bundle small data files of any type into larger units - mounted collections. The system can create collection families and contains its' own extensible metadata, including metadata on which family the collection belongs to. The mounted collection system can work standalone and is being incorporated into the iRODS system to enhance the systems flexibility to handle small files.In this paper we describe the motivation for creating a mounted collection system, its' architecture and how it has been incorporated into the iRODS system. We describe different technologies used to create the mounted collection system and provide some performance numbers.
On Clifford neurons and Clifford multi-layer perceptrons
Authors: Sven Buchholz, Gerald Sommer
Venue: Neural Networks (2008)

We study the framework of Clifford algebra for the design of neural architectures capable of processing different geometric entities. The benefits of this model-based computation over standard real-valued networks are demonstrated. One particular example thereof is the new class of so-called Spinor Clifford neurons. The paper provides a sound theoretical basis to Clifford neural computation. For that purpose the new concepts of isomorphic neurons and isomorphic representations are introduced. A unified training rule for Clifford MLPs is also provided. The topic of activation functions for Clifford MLPs is discussed in detail for all two-dimensional Clifford algebras for the first time.
The Case for Frame-Based Software Engineering
Authors: Paul G. Bassett
Venue: IEEE Software (2007)

A frame is an archetype—a model from which all similar things are made. Frame technology can synthesize any information structure (such as a program) from machine-adaptable frames. The author contrasts FT with object-oriented classes. By canonically defining each information structure in terms of its unique properties, frames avoid the complexities induced by code-level redundancies. Frames also solve the problem of how to regenerate domain-specific-language programs without destroying prior customizations. The article includes evidence of FT's efficacy, its impact on software's life cycle, elements of frame design, and an easy way to get started.
Applying Web 2.0 Design Principles in the Design of Cooperative Applications
Authors: Niels Pinkwart
Venue: Proceedings of the 5th international conference on Cooperative Design, Visualization, and Engineering (2008)

"Web 2.0" is a term frequently mentioned in media - apparently, applications such as Wikipedia, Social Network Services, Online Shops with integrated recommender systems, or Sharing Services like flickr, all of which rely on user's activities, contributions, and interactions as a central factor, are fascinating for the general public. This leads to a success of these systems that seemingly exceeds the impact of most "traditional" groupware applications that have emerged from CSCW research. This paper discusses differences and similarities between novel Web 2.0 tools and more traditional CSCW application in terms of technologies, system design and success factors. Based on this analysis, the design of the cooperative learning application LARGO is presented to illustrate how Web 2.0 success factors can be considered for the design of cooperative environments.
Context-Aware Loading for Mobile Applications
Authors: Markus Aleksy, Thomas Butter, Martin Schader
Venue: Proceedings of the 2nd international conference on Network-Based Information Systems (2008)

The dynamic adaptability to the current context of the user is one of the most important challenges to a context-aware mobile application since context decides on the available services. In this paper, we present an approach, which supports dynamic loading of the different elements of a mobile application. This includes context sensors, adapted input and output components, or the business logic required for the use of a context-aware service.
BIRADS Classification in Breast Tomosynthesis Compared to Mammography and Ultrasonography
Authors: Anders Tingberg, Ingvar Andersson, Debra M Ikeda, Mark Ruschin, Tony Svahn, Pontus Timberg
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

This paper presents the Malmö Breast Tomosynthesis project. The tomosynthesis equipment is described as well as the patient selection and image acquisition. Special focus is given to one of the studies of the project, which is a comparison of the diagnostic performance between breast tomosynthesis (BT), digital mammography (DM) and ultrasonography (US): Tumor classification according to the BIRADS system was performed on 40 cancers imaged with DM, US and BT. The patients were selected on the basis of subtle signs of breast cancer on DM or negative findings on DM but suspicious lesions on US. The BIRADS scores based on the BT images were significantly higher than 1-view DM and 2-view DM, and equal to 2-view plus US. The results suggest that BT may be a suitable technique for breast cancer screening.
R-PLUS: A Riemannian Anisotropic Edge Detection Scheme for Vascular Segmentation
Authors: Ali Gooya, Takeyoshi Dohi, Ichiro Sakuma, Hongen Liao
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

In this paper, detection of edges in oriented fields is addressed. In some applications such as vessel segmentation because of the intrinsic orientation of the structures, edge detection is only demanded in a particular subspace. This is specially usefull when a curve evolution is chosen for segmentation since gradients in parallel to vessel orientation may stop the contour. An anisotropic edge detection scheme is generalized on a Riemannian manifold using the local structure tensor. The method is the generalization of the PLUS operator proposed in [8] for accurate curved edge detection. Examples are given and the comparison is made with the state-of-the-art flux maximizing flow which indicates that significant improvements in terms of leakage minimization and thiner vessel delineation is achievable using our methodology.
Autonomous Planned Color Learning on a Legged Robot
Authors: Mohan Sridharan, Peter Stone
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

Our research focuses on automating the color-learning process on-board a legged robot with limited computational and memory resources. A key defining feature of our approach is that instead of using explicitly labeled training data it trains autonomously and incrementally, thereby making it robust to re-colorings in the environment. Prior results demonstrated the ability of the robot to learn a color map when given an executable motion sequence designed to present it with good color-learning opportunities based on the known structure of its environment. This paper extends these results by demonstrating that the robot can plan its own such motion sequence and perform just as well at color-learning. The knowledge acquired at each stage of the learning process is used as a bootstrap mechanism to aid the robot in planning its motion during subsequent stages.
Question Answering with Joost at CLEF 2007
Authors: Gosse Bouma, Geert Kloosterman, Jori Mur, Gertjan Noord, Lonneke Plas, Jörg Tiedemann
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

We describe our system for the monolingual Dutch and multilingual English to Dutch QA tasks. We describe the preprocessing of Wikipedia, inclusion of query expansion in IR, anaphora resolution in follow-up questions, and a question classification module for the multilingual task. Our best runs achieved 25.5% accuracy for the Dutch monolingual task, and 13.5% accuracy for the multilingual task.
Combination of SOM and RBF Based on Incremental Learning for Acoustic Fault Identification of Underwater Vehicles
Authors: Song Tu, Kerong Ben, Liye Tian, Linke Zhang
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

Lots of growing neural network models have been proposed to tackle the incremental learning problem, but they also bring about the problem of fast growing complex structure. In this paper, we present a combinational Neural Network of SOM (Self-Organizing Maps) and RBF (Radial Basis Function) based on incremental learning method. The experiment of acoustic fault sources identification of underwater vehicle shows that the proposed network has better generalization performance than traditional RBF network, and can improve the speed and accuracy of identification.
A perturbative approach to the critical time durations in quantum optimal control for multivariate harmonic oscillator
Authors: Esma Meral, Metin Demiralp
Venue: Proceedings of the 1st WSEAS International Conference on Multivariate Analysis and its Application in Science and Engineering (2008)

This work is devoted to find the critical time instants for a multivariate quantum harmonic oscillator system under optimal control. All quantum optimal control agents are taken linear in their arguments. The objective operator and the operator whose expectation value is to be suppressed are expressed as linear combinations of the position and momentum operators. The external field influence on the system is approximated only by the dipole polarizability term and the dipole function is taken as a linear combination of the positions. These linearities together with the elastic force structure of the mutual interactions amongst the oscillators brings the whole linearity to the system. We do not concern with the wave and costate functions. Instead, the expectation values of the position and momenta are taken as unknowns together with the two way transitions between the states described by the wave and costate functions, through positions and momenta. The resulting control problem appears to be a boundary value problem in time through a vector valued ODE. The critical time durations of this equation are sought by expanding the deviation parameter with respect to a perturbation parameter. Perturbation terms for these critical time instants can be evaluated analytically.
Input Signals Normalization in Kohonen Neural Networks
Authors: Andrzej Bielecki, Marzena Bielecka, Anna Chmielowiec
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

In this paper a Kohonen self-organizing competitive algorithm is considered. A formal approach to classification problem, basing on equivalence relations, is proposed. The Kohonen neural networks are considered as classifying systems. The main topic of this paper is proposal of applying stereographic projection as an input signals normalization procedure. Both theoretical justification is discussed and results of experiments are presented. It turns out that the introduced normalization procedure is effective.
MetiTarski: An Automatic Prover for the Elementary Functions
Authors: Behzad Akbarpour, Lawrence C. Paulson
Venue: Proceedings of the 9th AISC international conference, the 15th Calculemas symposium, and the 7th international MKM conference on Intelligent Computer Mathematics (2008)

Many inequalities involving the functions ln, exp, sin, cos, etc., can be proved automatically by MetiTarski: a resolution theorem prover (Metis) modified to call a decision procedure (QEPCAD) for the theory of real closed fields. The decision procedure simplifies clauses by deleting literals that are inconsistent with other algebraic facts, while deleting as redundant clauses that follow algebraically from other clauses. MetiTarski includes special code to simplify arithmetic expressions.
A SPARQL Semantics Based on Datalog
Authors: Simon Schenk
Venue: Proceedings of the 30th annual German conference on Advances in Artificial Intelligence (2007)

SPARQL is the upcoming W3C standard query language for RDF data in the semantic web. In this paper we propose a formal semantics for SPARQL based on datalog. A mapping of SPARQL to datalog allows to easily reuse existing results from logics for analysis and extensions of SPARQL. Using this semantics we analyse the complexity of query answering in SPAQRL and propose two useful extensions to SPARQL, namely binding of variables to results of filter expressions and views on RDF graphs as datasets for queries. We show that these extensions to not add to the overall complexity of SPARQL.