[PDF] Top 20 Efficient inference in multi task Cox process models
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Efficient inference in multi task Cox process models
... Gaussian process prior ( gp , Williams and Ras- mussen, ...hard inference challenges due to its doubly-stochastic nature and the notorious scalability issues of gp ...scalable inference algorithms ... See full document
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Efficient Bayesian Inference of Sigmoidal Gaussian Cox Processes
... Gaussian inference algorithms are available which can be applied to arbitrary link–functions, the choice of link–functions is not only crucial for defining the prior over intensities but can also be important for ... See full document
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Multi-Task Learning for Classification with Dirichlet Process Priors
... logistic-regression models for multiple classification tasks, where the training data set for each task is not drawn from the same statistical ...a multi-task learning (MTL) scenario, it is ... See full document
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Generic Inference in Latent Gaussian Process Models
... is multi-class classification of handwriting digits on the mnist dataset using a softmax likelihood ...the task involves binary classification of odd and even digits using the logistic likelihood ...The ... See full document
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Bayesian Optimization for Policy Search via Online-Offline Experimentation
... the multi-task model in practice, and showed the relative values of online and simulator ...for multi-task learning, and that the theory could be used to guide decisions in sizing ... See full document
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Comparison of Artificial Neural Networks and Cox Regression Models in Prediction of Kidney Transplant Survival
... -1. Multi-layer perceptron ANN is mainly used for solving complicated problems due to its parallel valuable abilities and ...Learning process in these networks takes place through certain algorithms that ... See full document
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Sieg at MEDIQA 2019: Multi task Neural Ensemble for Biomedical Inference and Entailment
... a multi-task learning ap- proach to natural language inference (NLI) and question entailment (RQE) in the biomed- ical ...textual inference re- lations and question similarity can address the ... See full document
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Efficient and Scalable Multi-Task Regression on Massive Number of Tasks
... as Multi-task Learning (MTL) problems with a mas- sive number of tasks, as in retail and transportation ...Clustering Multi-Task regression Learning (CCMTL), which integrates with con- vex ... See full document
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BAYESIAN INFERENCE OF MULTINOMIAL DATA USING SEQUENTIAL UPDATING: A CASE STUDY OF THE NIGERIAN PRESIDENTIAL ELECTION
... Election is the formal process of selecting a person for public office by voting. It is often thought of that election is the very core of democracy which involves electing the decision makers and hence getting ... See full document
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Efficient QoS Based Tasks Scheduling using Multi-Objective Optimization for Cloud Computing
... platform, task scheduling is the most important concern that aims to ensure that user‟s requirement are properly and correctly satisfied by cloud ...the process of mapping or assigning task to the ... See full document
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Evolutionary Algorithm Based Multi-Objective Tasks Scheduling Algorithm in Cloud Computing
... platform, task scheduling is the most important concern that aims to ensure that user’s requirement are properly and correctly satisfied by cloud ...the process of mapping or assigning task to the ... See full document
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An efficient parallel algorithm for haplotype inference based on rule based approach and consensus methods.
... This thesis implements two new parallel algorithms based on consensus method. First approach parallelizes the consensus method; whereas, the second parallel algorithm implements an enhanced consensus method that improves ... See full document
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Joint Emotion Analysis via Multi-task Gaussian Processes
... As it was discussed in Section 4.3, we plan to further explore the possibility of using non- Gaussian likelihoods with the GP models. An- other research avenue we intend to explore is to employ multiple layers of ... See full document
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Cognitive control: componential or emergent?
... specifically task shifting) by supporting the activation of relevant task ...forward models (which predict the consequences of an action and which can therefore be used by sensory and motor systems ... See full document
15
Multi-task Sparse Structure Learning with Gaussian Copula Models
... From an MTL perspective, the two data sets have different levels of difficulty. North America data set has almost twice the number of tasks as compared to South America, so that we discuss the performance of MSSL in ... See full document
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Study and Software Implementation of Variational Bayesian Approach to Mixed Deterministic/Stochastic Fuzzy Models
... Bayesian Inference (VB) to structure optimization of Fuzzy System (Takagi-Sugeno fuzzy ...constructing models of software processes and ...fuzzy models and also helps in software developments of some ... See full document
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The RepEval 2017 Shared Task: Multi Genre Natural Language Inference with Sentence Representations
... Additional Rules We provide competitors with labeled training and development sets, and unla- beled test sets for which they must submit labels. The development sets are meant to be used for hyperparameter tuning and ... See full document
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GIRNet: Interleaved Multi-Task Recurrent State Sequence Models
... available models for labeling whole passages (say, with sentiments), which we would like to exploit toward better position-specific label inference (say, target-dependent sentiment ...position-sensitive ... See full document
8
Training Complex Models with Multi-Task Weak Supervision
... our multi-task aware approach leads to average gains of ...identifiable models of their accuracies, where a unique solu- tion cannot be ...user-specified task and dependency ... See full document
9
Deep Cascade Multi-Task Learning for Slot Filling in Online Shopping Assistant
... Hierarchy multi-task learning share parameters among dif- ferent tasks, and allow low-level tasks help adjust the re- sult of high-level target ...high-level task dramatically depends on low-level ... See full document
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