نتایج جستجو برای: batch and online learning

تعداد نتایج: 16981315  

Journal: :Computational Linguistics 2016
Daniel Ortiz-Martínez

We present online learning techniques for statistical machine translation (SMT). The availability of large training data sets that grow constantly over time is becoming more and more frequent in the field of SMT—for example, in the context of translation agencies or the daily translation of government proceedings. When new knowledge is to be incorporated in the SMT models, the use of batch lear...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه تربیت دبیر شهید رجایی - دانشکده علوم انسانی 1390

with the growth of more humanistic approaches towards teaching foreign languages, more emphasis has been put on learners’ feelings, emotions and individual differences. one of the issues in teaching and learning english as a foreign language is demotivation. the purpose of this study was to investigate the relationship between the components of language learning strategies, optimism, duration o...

1998
Ole Winther Sara A. Solla

In a Bayesian approach to online learning a simple paramet-ric approximate posterior over rules is updated in each online learning step. Predictions on new data are derived from averages over this posterior. This should be compared to the Bayes optimal batch (or ooine) approach for which the posterior is calculated from the prior and the likelihood of the whole training set. We suggest that min...

2013
Ann Clifton Max Whitney Anoop Sarkar

We introduce an online framework for discriminative learning problems over hidden structures, where we learn both the latent structure and the classifier for a supervised learning task. Previous work on leveraging latent representations for discriminative learners has used batch algorithms that require multiple passes though the entire training data. Instead, we propose an online algorithm that...

Journal: :Proceedings of the ... AAAI Conference on Artificial Intelligence 2022

Catastrophic forgetting is a key obstacle to continual learning. One of the state-of-the-art approaches orthogonal projection. The idea this approach learn each task by updating network parameters or weights only in direction subspace spanned all previous inputs. This ensures no interference with tasks that have been learned. system OWM uses performs very well against other systems. In paper, w...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه سمنان - دانشکده علوم انسانی 1393

learning-oriented assessment seeks to emphasise that a fundamental purpose of assessment should be to promote learning. it mirrors formative assessment and assessment for learning processes. it can be defined as actions undertaken by teachers and / or students, which provide feedback for the improvement of teaching and learning. it also contrasts with equally important measurement-focused appro...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه زنجان - دانشکده ادبیات و علوم انسانی 1392

abstract the present study investigated the effects of task types and involvement load hypothesis on incidental learning of 10 target words (tws) in junior high schools (jhss) in givi, ardabil. the tasks deployed in this study were two input-based tasks (reading plus dictionary use with an involvement index of 3, and reading plus gap-fill task with an involvement index of 2), and one output-ba...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه شهید چمران اهواز - دانشکده ادبیات و علوم انسانی 1386

the purpose of the present study is to find out whether bilinguals of khuzestan-arab origin or monolinguals of iranian origin code-switch during learning or speaking english and which group is more susceptible to code-switch. to this end, the students of 24 classes from high schools and pre- university centers were screened out, and interviewed and their voices and code-switchings were recorded...

2013
Paul Ruvolo

This paper develops an efficient online algorithm based on K-SVD for learning multiple consecutive tasks. We first derive a batch multi-task learning method that builds upon the K-SVD algorithm, and then extend the batch algorithm to train models online in a lifelong learning setting. The resulting method has lower computational complexity than other current lifelong learning algorithms while m...

2014
Paul Ruvolo Eric Eaton

This paper develops an efficient online algorithm for learning multiple consecutive tasks based on the KSVD algorithm for sparse dictionary optimization. We first derive a batch multi-task learning method that builds upon K-SVD, and then extend the batch algorithm to train models online in a lifelong learning setting. The resulting method has lower computational complexity than other current li...

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