37 citations · 122 across the 29 of their papers we have counts for
4 papers · 1 filter
Mixture of Expert/Imitator Networks: Scalable Semi-supervised Learning Framework
Shun Kiyono, Jun Suzuki, Kentaro Inui
The current success of deep neural networks (DNNs) in an increasingly broad range of tasks involving artificial intelligence strongly depends on the quality and quantity of labeled…
Pointwise HSIC: A Linear-Time Kernelized Co-occurrence Norm for Sparse Linguistic Expressions
Sho Yokoi, Sosuke Kobayashi, Kenji Fukumizu +2
In this paper, we propose a new kernel-based co-occurrence measure that can be applied to sparse linguistic expressions (e.g., sentences) with a very short learning time, as an alt…
Direct Output Connection for a High-Rank Language Model
Sho Takase, Jun Suzuki, Masaaki Nagata
This paper proposes a state-of-the-art recurrent neural network (RNN) language model that combines probability distributions computed not only from a final RNN layer but also from…
Interpretable Adversarial Perturbation in Input Embedding Space for Text
Motoki Sato, Jun Suzuki, Hiroyuki Shindo +1
Following great success in the image processing field, the idea of adversarial training has been applied to tasks in the natural language processing (NLP) field. One promising appr…