Adversarial Learning
Adversarial Learning Based Semantic Correlation Representation for Cross-Modal Retrieval
... subspace learning method by integrating structured sparsity regularization and intra-modal information to achieve better ...and adversarial learning method to learn better representations with ...
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Multi turn Dialogue Response Generation in an Adversarial Learning Framework
... We propose an adversarial learning approach for generating multi-turn dialogue responses. Our proposed framework, hredGAN, is based on conditional generative adversarial networks (GANs). The GAN’s ...
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Deep Adversarial Learning for NLP
... deep learning extensions such as Generative Adversarial Networks (Goodfellow et ...deep adversarial learning in NLP listed ...of adversarial exam- ples and their uses in NLP tasks, ...
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MEAL: Multi-Model Ensemble via Adversarial Learning
... use adversarial-based learning strategy where we define a block-wise training loss to guide and optimize the predefined student network to recover the knowledge in teacher models, and to promote the ...
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KBGAN: Adversarial Learning for Knowledge Graph Embeddings
... the adversarial learning approach with a set of KGE ...versarial learning mechanism can significantly im- prove the performance of some of the most com- monly used translation based KGE ...
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On Committee Representations of Adversarial Learning Models for Question Answer Ranking
... vanilla adversarial learning provides a significant boost in model per- formance for Match Pyramid and Deep Match- ing Network, the performance boost by adversar- ial committee learning was much ...
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Transferable End to End Aspect based Sentiment Analysis with Selective Adversarial Learning
... Joint extraction of aspects and sentiments can be effectively formulated as a sequence label- ing problem. However, such formulation hin- ders the effectiveness of supervised methods due to the lack of annotated sequence ...
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A Unified Multi task Adversarial Learning Framework for Pharmacovigilance Mining
... tional adversarial learning component, where fea- ture extractor (Generator) is working operates ad- versarially towards a learnable multi-layer percep- tron (Discriminator), preventing it from making an ...
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Cyberspace Security Using Adversarial Learning and Conformal Prediction
... of adversarial learning include the digital analog of immune disease and immunosuppression using sensitivity analysis driven by cohorts and NCM related ...
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Image Aesthetic Assessment Assisted by Attributes through Adversarial Learning
... the adversarial learning closes the distributions between the predictions and ground truth ...through adversarial learning and achieves better performance than Malu et ...
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DAL: Dual Adversarial Learning for Dialogue Generation
... Dual Adversarial Learn- ing (DAL) for high-quality response genera- ...uses adversarial learning to mimic human judges and guides the system to generate natural ...
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Improving Hypernymy Prediction via Taxonomy Enhanced Adversarial Learning
... training. Adversarial learning is frequently applied in image generation (Goodfellow et ...NLP, adversarial learning makes less ...employ adversarial training in a multitask ...
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Robust Semantic Parsing with Adversarial Learning for Domain Generalization
... In this section, we focus on the Frame Argu- ment (or FE for Frame Element) Identification level, and propose contrastive experiments follow- ing the complexity factors analysis proposed by (Marzinotto et al., 2018b). In ...
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Adversarial Learning of Semantic Relevance in Text to Image Synthesis
... CGAN is fundamental to many approaches for text-to-image synthesis. Conditioning gives a means to control the genera- tive process that the original GAN lacks. Reed et al. (2016b) were the first to propose the ...
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Adversarial Learning for Weakly-Supervised Social Network Alignment
... according to neighborhood-based network features. CosNet (Zhang et al. 2015) was an energy-based model to link user identities by considering both local and global consistency. Existing semi-supervised methods usually ...
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An Adversarial Learning Framework For A Persona Based Multi Turn Dialogue Model
... which in addition to the adversarial discrimi- nator, collaboratively predicts the attribute(s) that generated the input utterance. To demon- strate the superior performance of phredGAN over the persona Seq2Seq ...
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Adversarial Learning for Neural Dialogue Generation
... forcement learning (RL) problem where we jointly train two systems, a generative model to produce response sequences, and a discriminator—analagous to the human evaluator in the Turing test— to distinguish between ...
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Static Prediction Games for Adversarial Learning Problems
... The conditions of Assumption 2 impose rather technical limitations on the cost functions. The requirement of convexity is quite ordinary in the machine learning context. In addition, the loss function has to be ...
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Adversarial Label Learning
... of adversarial learning has recently be- come popular for deep learning (Goodfellow et ...Generative adversarial networks (GANs) pit a data genera- tor and a discriminator against each other ...
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Learning Resolution-Invariant Deep Representations for Person Re-Identification
... of adversarial learning, we aim at extracting resolution-invariant representations for re-ID, while the pro- posed model is learned in an end-to-end training ...
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