A Specific and Selective Neural Response Representation With Decorrelating Auto-Encoder
نویسندگان
چکیده
منابع مشابه
The Diagnosis of Brucellosis in Rafsanjan City Using Deep Auto-Encoder Neural Networks
Introduction: Brucellosis is considered as one of the most important common infectious diseases between humans and animals. Considering the endemic nature of brucellosis and the existence of numerous reports of human and animal cases of brucellosis in Iran, the incidence of human brucellosis in Rafsanjan city was determined in the last 3 years (2016–2018). The main objective of this study was t...
متن کاملNeural evidence for representation-specific response selection.
Response selection is the mental process of choosing representations for appropriate motor behaviors given particular environmental stimuli and one's current task situation and goals. Many cognitive theories of response selection postulate a unitary process. That is, one central response-selection mechanism chooses appropriate responses in most, if not all, task situations. However, neuroscienc...
متن کاملStructured Auto-Encoder
In this work, we present a technique that learns discriminative audio features for Music Information Retrieval (MIR). The novelty of the proposed technique is to design auto-encoders that make use of data structures to learn enhanced sparse data representations. The data structure is borrowed from the Manifold Learning field, that is data are supposed to be sampled from smooth manifolds, which ...
متن کاملAuto-encoder pre-training of segmented-memory recurrent neural networks
The extended Backpropagation Through Time (eBPTT) learning algorithm for Segmented-Memory Recurrent Neural Networks (SMRNNs) yet lacks the ability to reliably learn long-term dependencies. The alternative learning algorithm, extended Real-Time Recurrent Learning (eRTRL), does not suffer this problem but is computational very intensive, such that it is impractical for the training of large netwo...
متن کاملAuto-JacoBin: Auto-encoder Jacobian Binary Hashing
Binary codes can be used to speed up nearest neighbor search tasks in large scale data sets as they are efficient for both storage and retrieval. In this paper, we propose a robust auto-encoder model that preserves the geometric relationships of high-dimensional data sets in Hamming space. This is done by considering a noise-removing function in a region surrounding the manifold where the train...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2019
ISSN: 2169-3536
DOI: 10.1109/access.2019.2918692