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In this paper, we propose (1) a novel theoretical framework that can be applied to a wide family of structured prediction settings able to capture potential local structure in the

We will show that most loss functions used in machine learning and structured prediction settings indeed satisfy the ILE property and therefore that the learning framework proposed

In a series of recent theoretical works, it was shown that strongly over- parameterized neural networks trained with gradient-based methods could converge exponentially fast to

Abstract: New theoretical and applied aspects of software engineering are introduced, viz.: technologies of developing programs and reusable components with MS.NET, CORBA,

Qual Rank (w/out DQs) Qualifying Position Best Time secs max head-to-head victory margin.. BestTime TotalTimeRankTotalTimew/DQTied-atTimeTied-atTimeRankRun1Timew/DQRun2Timew/DQ

As a conclusion, the Markov Monoid Algorithm introduced in [FGO12], used to decide the value 1 problem for leaktight automata, is actually the most correct algorithm known so far,

In Chapter 5 , we introduced the WELDON architecture, which is composed of two sub-networks: a deep feature extraction net- work based on VGG16 and a prediction network based on