134 citations · 459 across the 38 of their papers we have counts for
5 papers · 1 filter
Towards Zero-Shot Learning with Fewer Seen Class Examples
Vinay Kumar Verma, Ashish Mishra, Anubha Pandey +2
We present a meta-learning based generative model for zero-shot learning (ZSL) towards a challenging setting when the number of training examples from each \emph{seen} class is ver…
Generalized Adversarially Learned Inference
Yatin Dandi, Homanga Bharadhwaj, Abhishek Kumar +1
Allowing effective inference of latent vectors while training GANs can greatly increase their applicability in various downstream tasks. Recent approaches, such as ALI and BiGAN fr…
P-SIF: Document Embeddings Using Partition Averaging
Vivek Gupta, Ankit Saw, Pegah Nokhiz +3
Simple weighted averaging of word vectors often yields effective representations for sentences which outperform sophisticated seq2seq neural models in many tasks. While it is desir…
Quantile Regularization: Towards Implicit Calibration of Regression Models
Saiteja Utpala, Piyush Rai
Recent works have shown that most deep learning models are often poorly calibrated, i.e., they may produce overconfident predictions that are wrong. It is therefore desirable to ha…
A "Network Pruning Network" Approach to Deep Model Compression
Vinay Kumar Verma, Pravendra Singh, Vinay P. Namboodiri +1
We present a filter pruning approach for deep model compression, using a multitask network. Our approach is based on learning a a pruner network to prune a pre-trained target netwo…