1,129 research outputs found
Crosstalk [7] channels AdaBoost INRIA DBN-Isol [22] HOG DeepNet INRIA DBN-Mut [25] HOG DeepNet INRIA/Caltech
No full textfeatures classifier training notes ACF [11] channels AdaBoost INRIA evolution of ChnFtrs [source code] ACF-Caltech [11] channels AdaBoost Caltech evolution of ChnFtrs [source code] ACF+SDt [28] channels AdaBoost Caltech SDt = Stabilized Dt (motion features) AFS [14] multiple linear SVM INRIA accelerated version of FeatSynth AFS+Geo [14] multiple linear SVM INRIA variant of AFS with geometry constraints ChnFtrs [10] channels AdaBoost INRIA updated (see addendum on author website) ConvNet [31] pixels DeepNet INRI
Cartolabe Inria 2000-2022
No full textCartolabe Inria 2000-2022 dataset is generated using cartolabe-data with the data extracted from the HAL open archive which stores scholarly documents from all academic fields. We've filtered this dataset to include all articles published by authors from Inria (National Institute for Research in Digital Science and Technology) between 2000 and 2022.Provides year, lab, author and word filters. Besides provides the CSV file used to generate the export.feather file
INRIA PhD fellowship on Nonlinear speech analysis for differential diagnosis between Parkinson's disease and Multiple-System Atrophy
No full textProposal for an INRIA PhD fellowship (Cordi-S) Title of the proposal: Nonlinear speech analysis for differential diagnosis between Parkinson's disease and Multiple-System Atrophy Project Team INRIA: GeoStat (http://geostat.bordeaux.inria.fr/) Author of the proposal research subject: Khalid Daoudi (khalid.daoudi @ inria.fr) Keywords: speech processing, nonlinear speech analysis, machine learning, voice pathology, dysphonia, dysarthria, Multiple-System Atrophy, Parkinson's disease. Scientific c..
Rough And Modal Algebras
No full textWe have used here a theorem prover DATAC (D#duction Automatique dans des Th#ories Associatives et Commutatives) to discover, study and compare properties of rough and corresponding modal algebras. The preliminary results were reported in [19]. The prover was developed at CRIN & INRIA Lorraine, Nancy (France), by the ørst author. The rough algebras were introduced by the second author in [17] as a generalization of rough algebra of formulas of a modal logic S5, deøned and examined in [1]. The rough algebras provide a mathematical characterization of a notion of rough equality introduced by Pawlak in 1985 ([7]). The modal algebras were introduced by McKinsey and Tarski in [4] under the name of closure algebras. They were ørst (algebraic) models for modal logics S4 and S5, as opposed to Kripke models invented some 20 years later ([3]). We also present here some detailed proofs chosen out of thousands proofs of theorems discovered and proved automatically by the theorem prover. 1. INTROD..
On relationship between term rewriting systems and regular tree languages
No full textProjet EURECAIf P is a set of open terms, Red(P) is the set of terms that contain at least a subterm which is an instance of a term in P. The main theorem of this paper says that if L is a regular language of ground terms and P is a finite set of open terms such that L \subseteq Red(P), then there exists a finite set P* such that all the terms of P* are linear instances of terms in P and L \subseteq Red(P*). Applications of this result to ground reducibility of term rewrite systems are also discussed. This work was done while the author was visiting INRIA-Lorraine
Fast Multipattern Matching for Intrusion Detection
No full textM. Rusinowitch is senior researcher at INRIA. He got a Ph.D. in Computer Science at Nancy in 1987. He is now leader of the CASSIS research team of INRIA-Lorraine with about 20 members, whose activities are focused on automated deduction, software verification and security. M. Rusinowitch’s research is concerned with the automated detection of flaws in software using symbolic analysis techniques. He is the author or coauthor of more than 22 papers in journals and 50 papers in conference and is the author of a book. He is also cochairman of the next IJCAR conference to be held in 2004 at Cork and PC member of several events in automated deduction and security
Optimal solution error covariance in highly nonlinear problems of variational data assimilation
No full textThe problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem (see, e.g.[1]) to find the initial condition, boundary conditions or model parameters. The input data contain observation and background errors, hence there is an error in the optimal solution. For mildly nonlinear dynamics, the covariance matrix of the optimal solution error can be approximated by the inverse Hessian of the cost functional of an auxiliary data assimilation problem ([2], [3]). The relationship between the optimal solution error covariance matrix and the Hessian of the auxiliary control problem is discussed for different degrees of validity of the tangent linear hypothesis. For problems with strongly nonlinear dynamics a new statistical method based on computation of a sample of inverse Hessians is suggested. This method relies on the efficient computation of the inverse Hessian by means of iterative methods (Lanczos and quasi-Newton BFGS) with preconditioning. The method allows us to get a sensible approximation of the posterior covariance matrix with a small sample size. Numerical examples are presented for the model governed by Burgers equation with a nonlinear viscous term. The first author acknowledges the funding through the project 09-01-00284 of the Russian Foundation for Basic Research, and the FCP program "Kadry"
Combinatorial Optimization Problems for Which Almost Every Algorithm is Asymptotically Optimal
No full textConsider a class of optimization problems for which the cardinality of the set of feasible solutions is m and the size of every feasible solution is N . We prove in a general probabilistic framework that the value of the optimal solution and the value of the worst solution are asymptotically almost surely (a.s.) the same provided log m = o(N) as N and m become large. This result implies that for such a class of combinatorial optimization problems almost every algorithm finds asymptotically optimal solution! The quadratic assignment problem, the location problem on graphs, and a pattern matching problem fall into this class. This research was primary done while the author was visiting INRIA, Rocquencourt, France, and he wishes to thank INRIA (projects ALGO, MEVAL and REFLECS) for a generous support. In addition, support was provided by NSF Grants CCR-9201078, NCR-9206315 and INT-8912631, by Grant AFOSR-90-0107, and in part by NATO Collaborative Grant 0057/89. 1. INTRODUCTION We co..
Clustering and Sharing Incentives in BitTorrent Systems
No full textThis article is the author version of a paper accepted at ACM SIGMETRICS'2007. In particular, this paper is different from the technical report inria-00112066, version 1 - 21 November 2006. The technical report inria-00112066, version 1 - 21 November 2006 is a extended version of this paper (same title and authors, but different content) Version 2 is the same content as version 1, but with a different class in order to match the camera ready format for SIGMETRICSPeer-to-peer protocols play an increasingly instrumental role in Internet content distribution. It is therefore important to gain a complete understanding of how these protocols behave in practice and how their operating parameters affect overall system performance. This paper presents the first detailed experimental investigation of the peer selection strategy in the popular BitTorrent protocol. By observing more than 40 nodes in instrumented private torrents, we validate three protocol properties that, though believed to hold, have not been previously demonstrated experimentally: the clustering of similar-bandwidth peers, the effectiveness of BitTorrent's sharing incentives, and the peers' high uplink utilization. In addition, we observe that BitTorrent's modified choking algorithm in seed state provides uniform service to all peers, and that an underprovisioned initial seed leads to absence of peer clustering and less effective sharing incentives. Based on our results, we provide guidelines for seed provisioning by content providers, and discuss a tracker protocol extension that addresses an identified limitation of the protocol
Elements of a scientific communication policy
No full textInternational audienceThe development of open access in France has since long been leaning towards a green (i.e. deposit in publication repositories) preference. This has been reflected recently in the debates around the Loi pour une République Numérique where the focus has been put on embargoes and re-use rights for data mining activities. Inria, the national research organisation for computer science and applied mathematics, has gone even further by implementing a deposit mandate associated to a very cautious policy with regards author-pays publication models. In our talk, we will present the tenets for such a policy, advocating the need to have a coherent vision of the future of scientific communication comprising such aspects as document format, licences, certification, hosting, authorities, etc
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