Neil Hurley
University College Dublin, Computer Science and Informatics, Faculty Member
Research Interests:
Abstract The vulnerability of quantization-based data hiding methods to amplitude scaling requires the formulation of countermeasures to this relatively simple attack. Rational dither modulation (RDM) was recently proposed as a... more
Abstract The vulnerability of quantization-based data hiding methods to amplitude scaling requires the formulation of countermeasures to this relatively simple attack. Rational dither modulation (RDM) was recently proposed as a quantization-based data hiding scheme, which is scaling invariant. This is achieved by a simple modification of the well-known dither modulation (DM) data hiding method. The performance of RDM, asymptotically in the memory size of the system, can be made to approach that of DM on the Gaussian channel. ...
Research Interests:
Abstract Standard top-N collaborative recommendation algorithms are very poor at recommending relevant products to a user that are more novel than her average tastes. Our study shows that novel recommendation is difficult because standard... more
Abstract Standard top-N collaborative recommendation algorithms are very poor at recommending relevant products to a user that are more novel than her average tastes. Our study shows that novel recommendation is difficult because standard similarity metrics measure the aggregate similarity to multiple items in the user profile and the influence of more novel items is lost in the aggregation. To better capture the user's range of tastes, we propose to partition the user profile into clusters of similar items and compose the ...
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Research Interests:
Research Interests:
An efficient MCMC algorithm is presented to cluster the nodes of a network such that nodes with similar role in the network are clustered together. This is known as block-modelling or block-clustering. The model is the stochastic... more
An efficient MCMC algorithm is presented to cluster the nodes of a network such that nodes with similar role in the network are clustered together. This is known as block-modelling or block-clustering. The model is the stochastic blockmodel (SBM) with block parameters integrated out. The resulting marginal distribution defines a posterior over the number of clusters and cluster memberships. Sampling from this posterior is simpler than from the original SBM as transdimensional MCMC can be avoided. The algorithm is based on the allocation sampler. It requires a prior to be placed on the number of clusters, thereby allowing the number of clusters to be directly estimated by the algorithm, rather than being given as an input parameter. Synthetic and real data are used to test the speed and accuracy of the model and algorithm, including the ability to estimate the number of clusters. The algorithm can scale to networks with up to ten thousand nodes and tens of millions of edges.
Résumé/Abstract The vulnerability of quantization-based data hiding schemes to amplitude scaling requires the formulation of countermeasures to this relatively simple attack. Parameter estimation is one possible approach, where the... more
Résumé/Abstract The vulnerability of quantization-based data hiding schemes to amplitude scaling requires the formulation of countermeasures to this relatively simple attack. Parameter estimation is one possible approach, where the applied scaling is estimated from the received signal at the decoder. This estimate can be used to correct the mismatch with respect to the quantization step assumed by the decoder prior to decoding. In this work we present a method for joint iterative decoding and maximum likelihood estimation of the ...
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Research Interests:
ABSTRACT The application of error correction coding to side-informed watermarking utilizing polynomial detectors is investigated. The overall system is viewed as a code concatenation in which the outer code is a powerful channel code and... more
ABSTRACT The application of error correction coding to side-informed watermarking utilizing polynomial detectors is investigated. The overall system is viewed as a code concatenation in which the outer code is a powerful channel code and the inner code is a low rate repetition code. For the inner code we adopt our previously proposed side-informed embedding scheme in which the watermark direction is set to the gradient of the detection function in order to reduce the effect of host signal interference. Turbo codes are ...
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Research Interests:
Résumé/Abstract In this paper we present a statistical analysis of a particular audio fingerprinting method proposed by Haitsma et al [1]. Due to the excellent robustness and synchronisation properties of this particular fingerprinting... more
Résumé/Abstract In this paper we present a statistical analysis of a particular audio fingerprinting method proposed by Haitsma et al [1]. Due to the excellent robustness and synchronisation properties of this particular fingerprinting method, we would like to examine its performance for varying values of the parameters involved in the computation and ascertain its capabilities. For this reason, we pursue a statistical model of the fingerprint (also known as a hash, message digest or label). Initially we follow the work of a previous ...
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In the model-based clustering of networks, blockmodelling may be used to identify roles in the network. We identify a special case of the Stochastic Block Model (SBM) where we constrain the cluster-cluster interactions such that the... more
In the model-based clustering of networks, blockmodelling may be used to identify roles in the network. We identify a special case of the Stochastic Block Model (SBM) where we constrain the cluster-cluster interactions such that the density inside the clusters of nodes is expected to be greater than the density between clusters. This corresponds to the intuition behind community-finding methods, where nodes tend to clustered together if they link to each other. We call this model Stochastic Community Finding (SCF) and present an efficient MCMC algorithm which can cluster the nodes, given the network. The algorithm is evaluated on synthetic data and is applied to a social network of interactions at a karate club and at a monastery, demonstrating how the SCF finds the 'ground truth' clustering where sometimes the SBM does not. The SCF is only one possible form of constraint or specialization that may be applied to the SBM. In a more supervised context, it may be appropriate to use other specializations to guide the SBM.
In this paper, we introduce novel neighbourhood forma- tion and similarity weight transformation schemes for automated col- laborative ltering systems. We dene prole utility, which models the usefulness of user proles for collaborative... more
In this paper, we introduce novel neighbourhood forma- tion and similarity weight transformation schemes for automated col- laborative ltering systems. We dene prole utility, which models the usefulness of user proles for collaborative ltering as a function of the items they contain. We demonstrate that our approach leads to more efcient and scalable collaborative ltering when compared to a benchmark
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Minnich & McKee [57] ABSTRACT Guidances are provided for database retrieval in a numerical simulation system. A user can execute numerical simulation without knowledge of mathematical and numerical techniques. A physical model... more
Minnich & McKee [57] ABSTRACT Guidances are provided for database retrieval in a numerical simulation system. A user can execute numerical simulation without knowledge of mathematical and numerical techniques. A physical model is generated using information of a region shape, material name, physical phenomenon name, boundary condition name, and the like, respectively inputted by a user. A mathematical model generating step calculates physical characteristic values from the physical model, and in accordance with the ...
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Research Interests:
Abstract. It has been established in recent work that collaborative recommender systems are vulnerable to attacks that seek to manipulate the recommendations that are made for target items. In this paper, we examine attacks from a cost... more
Abstract. It has been established in recent work that collaborative recommender systems are vulnerable to attacks that seek to manipulate the recommendations that are made for target items. In this paper, we examine attacks from a cost perspective. While various costs can be associated with attacks, here we focus on the effect that attack size, in terms of the number of ratings that are inserted during an attack, has on attack success. We present a cost-benefit analysis which shows that substantial profits can be realised by attackers, even when ...
Under perfect synchronisation conditions, watermark- ing schemes employing asymmetric spread-spectrum tech- niques are suitable for copy-protection of audio signals. This paper proposes to combine the use of a robust psychoacous- tic... more
Under perfect synchronisation conditions, watermark- ing schemes employing asymmetric spread-spectrum tech- niques are suitable for copy-protection of audio signals. This paper proposes to combine the use of a robust psychoacous- tic projection for the extraction of a watermark feature vec- tor along with non-linear detection functions optimised with side-information. The new proposed scheme benefits from an increased level of security
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ABSTRACT In this paper we attempt to retrieve the items in the long-tail for top-N recommendation. That is, to recommend products that the end-user likes, but that are not generally popular, which has been getting more and more notice... more
ABSTRACT In this paper we attempt to retrieve the items in the long-tail for top-N recommendation. That is, to recommend products that the end-user likes, but that are not generally popular, which has been getting more and more notice lately. By analysing the existing issue of current recommendation algorithms, a strategy is proposed that succeeds in maintaining recommendation accuracy while reducing the concentration of the recommendation on popular items in the system. Evaluating on the publicly available Movie lens and Yahoo! datasets, the results show the recommendation algorithm proposed in this work retrieves items in the users' relatively unpopular tastes without losing the performance in their popular tastes, which ultimately results in a better overall accuracy for the system.
Research Interests:
Research Interests:
Research Interests:
Google, Inc. (search). ...
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ABSTRACT EgoNav is a visual analytics system that characterizes egos based on the relationship structure of their egocentric networks and presents the results as a spatialization. An ego, or individual node in a network, is most closely... more
ABSTRACT EgoNav is a visual analytics system that characterizes egos based on the relationship structure of their egocentric networks and presents the results as a spatialization. An ego, or individual node in a network, is most closely related to its neighbors, and to a lesser degree, to its neighbor's neighbors. For example, in social networks, people are closely related to their friends and family. In financial networks, the affairs of borrowers and lenders are more closely tied to each other. In fact, the relationship structure surrounding an ego, or an egocentric network, can provide characteristic information about the ego itself. Using network motif analysis and dimensionality reduction techniques, the system places egos in similar areas of a spatialization if their egocentric networks are structurally similar. This view of a network discriminates between the various classes of typical and exceptional egos. We demonstrate its effectiveness using appropriate synthetic datasets, real-world mobile phone call and peer-to-peer lending datasets. We subsequently elicit user feedback from experts involved in the investigation of financial fraud to assess the tool's applicability in this domain.
Research Interests:
Wireless, Ad Hoc and Sensor Networks, and Distributed Coding Rate-Maximizing Multiuser Scheduling for Parallel Channel Access.................... Y. Ma, D. Zhang, and R. Schober 441 Fast DSP Algorithms, Transforms, and Computation Convolution Using Discrete Sine and Cosine Transforms................more
LETTERS Communication Signal Transmission, Reception, and Detection Row-Column Soft-Decision Feedback Algorithm for Two-Dimensional Intersymbol Interference ..................... ....... more
LETTERS Communication Signal Transmission, Reception, and Detection Row-Column Soft-Decision Feedback Algorithm for Two-Dimensional Intersymbol Interference ..................... .... .......................................................................................T.Cheng,BJBelzer,andK.Sivakumar ... An FFT-Based Method for Blind Identification of FIR SIMO Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ................................................................ S. Wang, J. Manton, DBH Tay, C. Zhang, and JC Devlin ... Wireless, Ad Hoc and Sensor Networks, and Distributed ...
MichaelO'Neill Artificial Intelligence and Cognitive Science-13th Irish Conference, AICS 2002. Limerick, Ireland, September 12-13, 2002. Proceedin/Sutcliffe, Richard FE/Ryan, Conor/Eaton, Malachy/Griffith, Niall JL On the Usefulness of Extracting Syntactic Dependencies for Text Indexing/Alonso, M...more
Lecture Notes in Computer Science, 2002(2464 ) Sumario. Título / Autor(es), Página(s). MichaelO'Neill Artificial Intelligence and Cognitive Science - 13th Irish Conference, AICS 2002 . Limerick, Ireland, September 12-13, 2002 .... more
Lecture Notes in Computer Science, 2002(2464 ) Sumario. Título / Autor(es), Página(s). MichaelO'Neill Artificial Intelligence and Cognitive Science - 13th Irish Conference, AICS 2002 . Limerick, Ireland, September 12-13, 2002 . Proceedin / Sutcliffe, Richard FE / Ryan, Conor / Eaton, Malachy / Griffith, Niall JL, On the Usefulness of Extracting Syntactic Dependencies for Text Indexing / Alonso, Miguel A / Vilares, Jesús / Darriba, Víctor M, 3-11. Using ...