28 citations · 85 across the 14 of their papers we have counts for
6 papers · 1 filter
Is Cross-modal Information Retrieval Possible without Training?
Hyunjin Choi, Hyunjae Lee, Seongho Joe +1
Encoded representations from a pretrained deep learning model (e.g., BERT text embeddings, penultimate CNN layer activations of an image) convey a rich set of features beneficial f…
Matrix Encoding Networks for Neural Combinatorial Optimization
Yeong-Dae Kwon, Jinho Choo, Iljoo Yoon +3
Machine Learning (ML) can help solve combinatorial optimization (CO) problems better. A popular approach is to use a neural net to compute on the parameters of a given CO problem a…
SelfMatch: Combining Contrastive Self-Supervision and Consistency for Semi-Supervised Learning
Byoungjip Kim, Jinho Choo, Yeong-Dae Kwon +3
This paper introduces SelfMatch, a semi-supervised learning method that combines the power of contrastive self-supervised learning and consistency regularization. SelfMatch consist…
DefogGAN: Predicting Hidden Information in the StarCraft Fog of War with Generative Adversarial Nets
Yonghyun Jeong, Hyunjin Choi, Byoungjip Kim +1
We propose DefogGAN, a generative approach to the problem of inferring state information hidden in the fog of war for real-time strategy (RTS) games. Given a partially observed sta…
VaB-AL: Incorporating Class Imbalance and Difficulty with Variational Bayes for Active Learning
Jongwon Choi, Kwang Moo Yi, Jihoon Kim +5
Active Learning for discriminative models has largely been studied with the focus on individual samples, with less emphasis on how classes are distributed or which classes are hard…
Multimodal Sparse Coding for Event Detection
Youngjune Gwon, William Campbell, Kevin Brady +3
Unsupervised feature learning methods have proven effective for classification tasks based on a single modality. We present multimodal sparse coding for learning feature representa…