two-level memory model
Major-minor long short-term memory for word-level language model
... language model called Major-Minor LSTMs (MMLSTMs), which employs two LSTMs of different scales to generate the output features ...language model without impairing the overall performance sig- ...
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The Role of Consciousness in Memory
... conceptual model, the repertoire of behavior codelets is also taken to be ...Thus, two distinct behavior streams may be partial plans with the same goal, but may employ different behaviors to get ...
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Multi Level Memory for Task Oriented Dialogs
... of memory in task oriented dialogue ...previous two datasets, this dataset contains di- alogs that require the agent to remember all infor- mation presented previously as well as support re- sults from ...
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A Modified Two Dimensional Volterra-Based Series for the Low-Pass Equivalent Behavioral Modeling of RF Power Amplifiers
... the memory length M ) samples of the complex-valued input ...proposed model starts from a general Volterra-based series given by the sum of contributions that include exactly one complex-valued information ...
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Dual Memory Network Model for Biased Product Review Classification
... dual memory network model for sentiment ...aggregated level. Based on this hypothesis, two separate memory networks for user context and product context are built at the document ...
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A Working Memory Model for Task oriented Dialog Response Generation
... encoder-decoder model, where decoder is the Working Memory (WM) which could in- teract with two long-term memories (the episodic memory memorizing dialog history and semantic memory ...
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Two Level Hierarchical Model of Load Balancing in Cloud
... a model in which Individual ants are behaviourally much unsophisticated ...limited memory and exhibit individual behaviour that appears to have a large random ...storage model and Storage as a ...
5
Abstractive Summarization of Reddit Posts with Multi level Memory Networks
... seq2seq model, two heuristic extractive methods and variants of our ...seq2seq model denoted as s2s-att (Chopra et ...our model as follows: (i) -NoDilated with conven- tional convolutions ...
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Gated Word Character Recurrent Language Model
... guage model (RNN-LM) with long short- term memory (LSTM) units that utilizes both character-level and word-level ...Our model has a gate that adaptively finds the op- timal mixture of ...
6
Document Context Neural Machine Translation with Memory Networks
... translation model which takes both source and target document context into account using memory ...We model the problem as a structured pre- diction problem with interdependencies among the observed ...
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Optimal Implementation of Two FIFO Queues in Single Level Memory
... Let two stacks grow towards each other in the shared memory of size ...mathematical model of this process [1]. In [2-6] a mathe- matical model of the process was constructed as two- ...
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Classification of Medication Related Tweets Using Stacked Bidirectional LSTMs with Context Aware Attention
... We train the model to minimize the negative log-likelihood loss using back-propagation with stochastic gradient descent and mini-batch size of 50. We use the Adam optimizer (Kingma and Ba, 2015) with gradient norm ...
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CONSISTENCY MODELS IN DISTRIBUTED SHARED MEMORY SYSTEMS
... remote memory is much slower than access to a local memory, and no attempt is made to hide this fact by hardware ...of two variations either way not being ...remote memory, but the program may ...
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An organizational learning model with respect to level of organizational culture within an organization and level of isomorphism between organizations
... The similarities caused by these processes allow firms to interact with each other more easily and to build legitimacy among organizations. This is different from coercive isomorphism because normative pressures are felt ...
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Bilinear Interpolation Image Scaling Processor for VLSI
... T- model filter as shown in Fig.3 To reduce the one-line- buffer memory, the only parameter in the third line, parameter −1 of P(i,j-2),is removed and the weight of parameter −1 is added into the parameter ...
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Dual drive tracking servomechanism
... plant noise is inevitable and a finite memory Kalman filter is called for, the system may then be remodelled as a combination of two systems, a deterministic model based on the measurabl[r] ...
246
Retrieve and Refine: Improved Sequence Generation Models For Dialogue
... Table 3 compares the word overlap between re- trieved and generated sentences in the RetNRef variants in order to measure if RetNRef is either ignoring the retriever, or else paying too much at- tention to and copying ...
6
Spell Once, Summon Anywhere: A Two-Level Open-Vocabulary Language Model
... recent past. As in Hwang and Sung (2017), there is no fixed vocabulary, so words that have fallen out of the cache have to be re-spelled. Our hierarchical generative story—specifically, the process that generates the ...
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TRANSFoRm : implementing a learning healthcare system in Europe through embedding clinical research into clinical practice
... the two-level modelling approach of DCM is depicted on the first level as an information model, the Clinical Research Information Model (CRIM) [20], which defines the workflow and data ...
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Commonsense knowledge enhanced memory network for stance classification
... used two bidirectional Recurrent Neural Network (RNN) to model both target and text for stance de- ...this model requires a very large unlabeled Twitter corpus in order to predict the task-relevant ...
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