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( Image credit: Prototypical Networks for Few shot Learning in PyTorch )

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Latest papers without code

One Model to Rule them All: Towards Zero-Shot Learning for Databases

3 May 2021

In this paper, we present our vision of so called zero-shot learning for databases which is a new learning approach for database components.

TRANSFER LEARNING ZERO-SHOT LEARNING

Learning Graph Embeddings for Open World Compositional Zero-Shot Learning

3 May 2021

In this work, we overcome this assumption operating on the open world setting, where no limit is imposed on the compositional space at test time, and the search space contains a large number of unseen compositions.

COMPOSITIONAL ZERO-SHOT LEARNING

A Framework for Unsupervised Classificiation and Data Mining of Tweets about Cyber Vulnerabilities

23 Apr 2021

Many cyber network defense tools rely on the National Vulnerability Database (NVD) to provide timely information on known vulnerabilities that exist within systems on a given network.

ZERO-SHOT LEARNING

Attribute-Modulated Generative Meta Learning for Zero-Shot Classification

22 Apr 2021

Our model consists of an attribute-aware modulation network and an attribute-augmented generative network.

CLASSIFICATION META-LEARNING ZERO-SHOT LEARNING

Imaginative Walks: Generative Random Walk Deviation Loss for Improved Unseen Learning Representation

20 Apr 2021

We propose a novel loss for generative models, dubbed as GRaWD (Generative Random Walk Deviation), to improve learning representations of unexplored visual spaces.

IMAGE GENERATION ZERO-SHOT LEARNING

CrossATNet - A Novel Cross-Attention Based Framework for Sketch-Based Image Retrieval

20 Apr 2021

While we define a cross-modal triplet loss to ensure the discriminative nature of the shared space, an innovative cross-modal attention learning strategy is also proposed to guide feature extraction from the image domain exploiting information from the respective sketch counterpart.

SKETCH-BASED IMAGE RETRIEVAL ZERO-SHOT LEARNING

Automated problem setting selection in multi-target prediction with AutoMTP

19 Apr 2021

AutoMTP is realized by adopting a rule-based system for the algorithm selection step and a flexible neural network architecture that can be used for the several subfields of MTP.

MATRIX COMPLETION MULTI-LABEL CLASSIFICATION MULTI-TARGET REGRESSION MULTI-TASK LEARNING ZERO-SHOT LEARNING

Data-Efficient Language-Supervised Zero-Shot Learning with Self-Distillation

18 Apr 2021

Our model transfers knowledge from pretrained image and sentence encoders and achieves strong performance with only 3M image text pairs, 133x smaller than CLIP.

ZERO-SHOT LEARNING

Does language help generalization in vision models?

16 Apr 2021

Vision models trained on multimodal datasets have recently proved very efficient, both in terms of the wide availability of large image-caption datasets, and in terms of the resulting model's ability to generalize to multiple downstream tasks (e. g. zero-shot learning).

FEW-SHOT LEARNING ZERO-SHOT LEARNING

Learning Robust Visual-semantic Mapping for Zero-shot Learning

12 Apr 2021

In ZSL, the common practice is to train a mapping function between the visual and semantic feature spaces with labeled seen class examples.

ZERO-SHOT LEARNING