Recently, distillation approaches for extracting general knowledge from a teacher network to guide student have been suggested. Most existing methods transfer the by feeding sequence of random minibatches sampled uniformly data. We argue that, instead, compact should be guided gradually using samples ordered in meaningful sequence. Thus, gap feature representation between and can bridged step s...

The ability to perform accurate sequential movements is essential to normal motor function. Learning a sequential motor behavior is comprised of two basic components: explicit identification of the order in which the sequence elements should be performed and implicit acquisition of spatial accuracy for each element. Here we investigated the time course of learning of these components for a firs...

Submodularity is an important  property of set functions with deep theoretical results  and various  applications. Submodular systems appear in many applicable area, for example machine learning, economics, computer vision, social science, game theory and combinatorial optimization.  Nowadays submodular functions optimization has been attracted by many researchers.  Pendant pairs of a symmetric...

In the Serial Reaction Time (SRT) task, participants respond to a set of stimuli the order of which is apparently random, but which consists of repeating sub-sequences. Participants can become sensitive to this regularity, as measured by an indirect test of reaction time, but can remain apparently unaware of the sequence, as measured by direct tests of prediction or recognition. Some researcher...

Empirical evidence suggests that levodopa medication used to treat the motor symptoms of Parkinson's disease (PD) may either improve, impair or not affect specific cognitive processes. This evidence led to the 'dopamine overdose' hypothesis that levodopa medication impairs performance on cognitive tasks if they recruit fronto-striatal circuits which are not yet dopamine-depleted in early PD and...

It has become widely accepted that sleep-dependent consolidation occurs for motor sequence learning based on studies using finger-tapping tasks. Studies using another motor sequence learning task [the serial response time task (SRTT)] have portrayed a more nuanced picture of off-line consolidation, involving both sleep-dependent and daytime consolidation, as well as modifying influences of expl...

Do you want your neural net algorithm to learn sequences? Do not limit yourself to conventional gradient descent (or approximations thereof). Instead, use your sequence learning algorithm (any will do) to implement the following method for history compression. No matter what your final goals are, train a network to predict its next input from the previous ones. Since only unpredictable inputs c...

We consider the application of machine learning techniques for sequence modeling to Information Retrieval (IR) and surface Information Extraction (IE) tasks. We introduce a generic sequence model and show how it can be used for dealing with different closed-query tasks. Taking into account the sequential nature of texts allows for a finer analysis than what is usually done in IR with static tex...

We examined the influence of task complexity on implicit sequence learning in secondary-school-aged children with developmental dyslexia (DD). This was done to determine whether automatization problems in reading extend to the automatization of all skill and depend on the complexity of the to-be-learned skill. A total of 28 dyslexic children between 12 and 15 years and 28 matched control childr...