[PDF] Top 20 Synthesizing Samples fro Zero shot Learning
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Synthesizing Samples fro Zero shot Learning
... labeled samples becomes an important and practi- cal problem and has gathered considerable research interests from the machine learning and computer vision ...many zero-shot learning ... See full document
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Zero Shot Cross Lingual Opinion Target Extraction
... supervised learning algorithms are usually em- ployed which are trained on manually anno- tated ...a zero-shot cross-lingual approach for the extraction of opinion target expres- ...annotated ... See full document
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From Zero-Shot Learning to Cold-Start Recommendation
... by learning from the train- ing ...training samples for new and rare objects is ...end, zero-shot learning (Zhang and Saligrama 2016; Ding, Shao, and Fu 2017) has been ...1) ... See full document
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Dual-View Ranking with Hardness Assessment for Zero-Shot Learning
... in zero-shot learning (ZSL) and there is an increasing num- ber of new ZSL approaches every year (Xian, Schiele, and Akata ...cal learning task in real-world applications, like Web-image ... See full document
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Semantic embeddings of generic objects for zero-shot learning
... training samples needed for efficient learning, few- shot learning techniques are being actively ...The zero-shot learning (ZSL) paradigm represents the extreme case of ... See full document
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Learning to Compose Topic-Aware Mixture of Experts for Zero-Shot Video Captioning
... ActivityNet (Fabian Caba Heilbron and Niebles 2015) is a well-known benchmark for video classification and detec- tion, which covers 200 classes of activities. Recently, (Kr- ishna et al. 2017) have collected the ... See full document
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Reconstructing Capsule Networks for Zero shot Intent Classification
... Several zero-shot learning approaches attempt- ed to address the challenges for classifying intents whose instances are not present during ...implement zero-shot intent classification ... See full document
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Zero shot Learning of Classifiers from Natural Language Quantification
... infinite samples. We note that LNQ is effective in learning competent classifiers for all levels of ...for learning easy concepts (towards the ... See full document
11
Energy Confused Adversarial Metric Learning for Zero-Shot Image Retrieval and Clustering
... metric learning for ZSRC: The commonly used contrastive (Sun et ...metric learning works: Smart-mining (Kumar et ...for learning discriminative ... See full document
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Extracting Commonsense Properties from Embeddings with Limited Human Guidance
... the zero-shot learning paradigm (Palatucci et ...the zero-shot setting in which we evaluate on properties not seen in ...in zero-shot, our approach outperforms baselines ... See full document
6
Zero shot Recognition via Direct Classifier Learning with Transferred Samples and Pseudo Labels
... select samples which are most similar to the target classes for a direct clas- sifier ...the samples into the attribute ...select samples for classifier training and we do not need them during the ... See full document
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Image Mediated Learning for Zero Shot Cross Lingual Document Retrieval
... We randomly sampled data from the dataset for each division in Table 1 without any overlap; we ignored the modality of each document that was not available in each data division (e.g., Japanese text in [train-E/I]). We ... See full document
6
Zero-Shot Object Detection with Textual Descriptions
... on zero-shot learning, object detection and language and ...literature. Zero-Shot Learning: Existing zero-shot learning algorithms exploit different methods ... See full document
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Gaussian Visual Linguistic Embedding for Zero Shot Recognition
... modal learning that aims to ground DSMs in non- linguistic modalities (Bruni et ...of zero-shot learning (ZSL). Zero-shot recognition aims to recognise visual categories in the ... See full document
7
Zero Shot Activity Recognition with Verb Attribute Induction
... for zero-shot learning (Marco and Geor- giana, 2015) and can be seen in our examples (for instance, the over-prediction of ...in zero-shot activity recognition as a question for future ... See full document
13
Zero Shot Relation Extraction via Reading Comprehension
... Experiments demonstrate that our approach generalizes to new paraphrases of questions from the training set, while incurring only a minor loss in performance (4% relative F1 reduction). Furthermore, translating relation ... See full document
10
Cross lingual Annotation Projection Is Effective for Neural Part of Speech Tagging
... The observations that have been made in the course of this work can be briefly summarized as follows: 1) Pre-trained word embeddings are im- portant for better tagging quality since they repre- sent contextual ... See full document
11
Grounding Semantics in Olfactory Perception
... for zero-shot learning, where the model can predict how an object relates to other concepts just from seeing an image of the object, but without ever having seen the object previously (Lazaridou et ... See full document
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Towards Fluid Machine Intelligence: Can We Make a Gifted AI?
... Work that directly takes the images and requires mini- mal human involvement has only recently been explored (Lovett and Forbus 2017). Some innovative work (McGreg- gor, Kunda, and Goel 2010) have realized that the ... See full document
5
Zero-Shot Learning of Language Models for Describing Human Actions Based on Semantic Compositionality of Actions
... al., 2012; Ding et al., 2012a; Ding et al., 2012b; Kobayashi et al., 2010; Kojima et al., 2002; Rohrbach et al., 2013; Tan et al., 2011). As representative studies, Yu and Siskind (2013) pro- pose a method that learns ... See full document
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