2021 Seminars


No.

Speaker

Title

Reference

Slides

Date

1

Mehret Abraha

Edge detection-based boundary box construction algorithm for improving

S. T. Blue, M. Brindha. Edge detection based boundary box construction algorithm for improving the precision of object detection in YOLOv3

PDF

Jan, 2021

2

Sanghyuck Na

MirrorGAN: Learning Text-to-image Generation
by Redescription

T. Qiao, J. Zhang, D. Xu, D. Tao. MirrorGAN: Learning Text-to-image Generation by Redescription

PDF

Jan, 2021

3

Sung-eun Jang

Few-shot link prediction via graph neural networks for covid-19 drug-repurposing

V. N. Ioannidis, D. Zheng, G. Karypis. Few-shot link prediction via graph neural networks for Covid-19 drug-repurposing

PDF

Feb, 2021

4

Anh Tran

Combining Deep Reinforcement Learning and Search for Imperfect-Information Games

N. Brown, A. Bakhtin, A. Lerer, Q. Gong. Combining Deep Reinforcement Learning and Search for Imperfect-Information Games

PDF

Feb, 2021

5

Park MinKyu

FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence

FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence

PDF

March, 2021

6

Mehret Abraha

Adversarial Network for edge detection

Z. Zeng, Y. Yu, K. Wong. Adversarial Network for edge detection

PDF

March, 2021

7

Sanghyuck Na

Tensor Fusion Network for Multimodal Sentiment Analysis

A. Zadeh, M. Chen et. al., Tensor Fusion Network for Multimodal Sentiment Analysis

PDF

April, 2021

8

Chang-Hoon Jeong

Deep Meta Learning Learning-to-Learn in Neural Networks

[Multiple Refrences]

PDF

April, 2021

9

Sung-eun Jang

Protein structure Prediction

[Multiple Refrences]

PDF

May, 2021

10

Anh Tran

Video Summarization Using Deep Neural Networks

E. Apostolids, E. Adamantidou et al. Video Summarization Using Deep Neural Networks

PDF

May, 2021

11

Sanghyun Seo

Meta-Information Guided Meta-Learning for Few-Shot Relation Classification

B. Dong, Y. Yao, R. Xie. Meta-Information Guided Meta-Learning for Few-Shot Relation Classification

PDF

May, 2021

12

Ershang Tian

Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection

S. Beery, G. Wu et al. Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection

PDF

May, 2021

13

Hiskias Dingeto

Eye In-Painting with Exemplar Generative Adversarial Networks

B, Dolhansky, C. Ferrer. Eye In-Painting with Exemplar Generative Adversarial Networks

PDF

June, 2021

14

Seoyeong Lee

A CNN­LST model for gold price time-series forecasting

I. Livieris, E. Pintelas, P. Pintelas. A CNN–LSTM model for gold price time-series forecasting

PDF

June, 2021

15

Beomsu Park

Deep Leakage from gradients

L. Zhu, Z. Liu, S. Han. Deep Leakage from Gradients

PDF

June, 2021

16

Mehret Abraha

Meta-Learning to Detect Rare Objects

Y. Wang, D. Ramanan, M. Hebert. Meta-Learning to Detect Rare Objects

PDF

July, 2021

17

Hiskias Dingeto

Targeted Speech Adversarial Example
Generation With Generative Adversarial Network

D. Wang et al. Targeted Speech Adversarial Example Generation With Generative Adversarial Network

PDF

July, 2021

18

Park MinKyu

MixBoost: Synthetic Oversampling using Boosted Mixup for Handling Extreme Imbalance

A. Kabea et al. MixBoost: Synthetic Oversampling with Boosted Mixup for Handling Extreme Imbalance

PDF

Aug, 2021

19

Anh Tran

Unsupervised Video Summarization with Adversarial LSTM Networks

B. Mahasseni et al. Unsupervised Video Summarization with Adversarial LSTM Networks

PDF

Aug, 2021

20

Ershang Tian

Meta-RCNN: Meta-Learning for Few-Shot Object Detection

X. Wu et al. Meta-RCNN: Meta-Learning for Few-Shot Object Detection

PDF

Aug, 2021

21

Seoyeong Lee

Playing Atari with Deep Reinforcement Learning

V. Mnih et al. Playing Atari with Deep Reinforcement Learning

PDF

Sept, 2021

22

Sujeong Chae

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

C. Finn et al. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

PDF

Sept, 2021

23

Hiskias Dingeto

Ensemble Adversarial Training: Attacks and Defenses

F. Tramer et al. Ensemble Adversarial Training: Attacks and Defenses

PDF

Sept, 2021

24

Mehret Abraha

Siamese Neural Networks for One-shot Image Recognition

G. Koch et al. Siamese Neural Networks for One-shot Image Recognition

PDF

Sept, 2021

25

Ershang Tian

Meta R-CNN : Towards General Solver for Instance-level Few-shot Learning

X. Yan et al. Meta R-CNN : Towards General Solver for Instance-level Few-shot Learning

PDF

Sept, 2021

26

Seoyeong Lee

Deep Recurrent Q-Learning for Partially Observable MDPs

M. Hausknecht et al. Deep Recurrent Q-Learning for Partially Observable MDPs

PDF

Dec, 2021

27

Sujeong Chae

Siamese Neural Networks for One-shot Image Recognition

G. Koch et al. Siamese Neural Networks for One-shot Image Recognition

PDF

Dec, 2021

2020 Seminars


No.

Speaker

Title

Reference

Slides

Date

1

Hyojin Ki

Attention Mechanism

D. Bahdanau, K. Cho, Y. Bengio. Neural Machine Translation by Jointly Learning to Align and Translate

PDF

Jan, 2020

2

Jonghyun Ko

Densely Connected Convolutional Networks (DenseNet)

G. Huang, Z. Liu, L. Maaten. Densely Connected Convolutional Networks

PDF

Jan, 2020

3

Sanghyun Seo

Meta Learning for Low-Resource
Natural Language Understanding

Z. Dou et al. Investigating Meta-Learning Algorithms for Low-Resource Natural Language Understanding Tasks, C. Finn et al. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

PDF

Feb, 2020

4

Park MinKyu

(Learning to) Learn from Unlabeled Data

Yalniz, I. Zeki, et al. Billion-scale semi-supervised learning for image classification

PDF

Feb, 2020

5

Changhoon Jeong

Meta Reinforcement Learning as Task Inference

J. Humplik, A. Galashov, L. Hasenclever, P. A. Ortega, Y. Teh, N. Heess. Meta Reinforcement Learning As Task Inference

PDF

Apr, 2020

6

Sung-eun Jang

Graph Neural Networks

Kipf, T. N., & Welling, M. (2016). Semi-supervised classification with graph convolutional networks, Hamilton, W., Ying, Z., & Leskovec, J. (2017). Inductive representation learning on large graphs, Veličković, P., Cucurull, G., Casanova, A., Romero, A., Lio, P., & Bengio, Y. Graph attention networks

PDF

Apr, 2020

7

Sanghyuck Na

StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks

H. Zhang, T. Xu, H. Li, S. Zhang, X. Wang, X. Huang, D. Metaxas. StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks

PDF

Apr, 2020

8

Daeung Kim

Transfer Learning in NLP

A. Chronopoulou, C. Baziotis, A. Potamianos. An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language Models

PDF

Apr, 2020

9

Sanghyuck Na

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

J. Johnson, A. Alahi, Li Fei-Fei. Perceptual Losses for Real-Time Style Transfer and Super-Resolution

PDF

May, 2020

10

Daeung Kim

Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks

T. Bansal, R. Jha, A. McCallum. Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks

PDF

June, 2020

11

Chea Navy

Transfer Learning & Domain Adaptation

S. J. Pan, Q. Y. Fellow. A Survey on Transfer Learning

PDF

July, 2020

12

Park MinKyu

MixMatch: A Holistic Approach to Semi-Supervised Learning

D. Berthelot, N. Carlini, I. Goodfellow, A. Oliver, N. Papernot, C. Raffel. MixMatch: A Holistic Approach to Semi-Supervised Learning

PDF

July, 2020

13

Yeonji Lim

Playing Atari with Deep Reinforcement Learning

V. Mnih, K. Kavukcuoglu, D. Silver, A. Graves, I. Antonoglou, D. Wierstra, M. Riedmiller. Playing Atari with Deep Reinforcement Learning

PDF

July, 2020

14

Mehret Abraha

You Only Look Once: Unified, Read Time Object Detection

J. Redmon, S. Divvala, R. Girshick, A. Farhad. You Only Look Once: Unified, Real-Time Object Detection

PDF

July, 2020

15

Sung-eun Jang

Edge-Labeling Graph Neural Network
for Few-shot Learning

J. Kim, T. Kim, S. Kim, C. D. Yoo. Edge-Labeling Graph Neural Network for Few-shot Learning

PDF

Aug, 2020

16

Shin SeungYun

GroupFace: Learning Latent Groups and Constructing Group-based Representations for Face Recognition

GroupFace: Learning Latent Groups and Constructing Group-based Representations for Face Recognition

PDF

Aug, 2020

17

Park MinKyu

Modern Data Augmentation Techniques

H. Zhang, M. Cisse, Y. N Dauphin, D. Lopez-Paz, “Mixup: Beyond empirical risk minimization,”, S. Yun, D. Han, S. Joon Oh, S. Chun, J. Choe, Y. Yoo, “Cutmix: Regularization strategy to train strong classifiers with localizable features,”

PDF

Sept, 2020

18

Daeung Kim

Multi-source Meta Transfer for Low Resource Multiple-Choice Question Answering

M. Yan, H. Zhang, D. Jin, J. T. Zhou. Multi-source Meta Transfer for Low Resource Multiple-Choice Question Answering

PDF

Sept, 2020

19

Anh Tran

Texas Hold’Em and Reinforcement Learning

X. C. Zhang, Y. Li. A Texas Hold’Em decision model based on Reinforcement Learning

PDF

Sept, 2020

20

Luna Jang

A Multiple Object Tracking Algorithm Based on YOLO Detection

L. Tan; X. Dong; Y. Ma, C. Yu. A Multiple Object Tracking Algorithm Based on YOLO Detection

PDF

Oct, 2020

21

Sung-eun Jang

Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-weighting

D. Liu, D. Zhang, Y. Song, F. Zhang, L. O'Donnell, H. Huang, M. Chen, W. Cai. Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-weighting

PDF

Nov, 2020

22

Sanghyuck Na

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

J. Zhu, T. Park, P. Isola, A. A. Efros. Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

PDF

Nov, 2020

2019 Seminars


No.

Speaker

Title

Reference

Slides

Date

1

Sanghyun Seo

Deep Metric Learning with Hierarchical Triplet Loss

Ge, Weifeng, et al. "Deep metric learning with hierarchical triplet loss." Proceedings of the European Conference on Computer Vision (ECCV). 2018

PDF

Jan, 2019

2

Park MinKyu

Zero-Shot Learning for Computer Vision

Zero-Shot Learning for Computer Vision, CVPR 2017

PDF

Jan, 2019

3

Hyojin Ki

Learning Deep Structure-Preserving
Image-Text Embeddings

Wang, Liwei, Yin Li, and Svetlana Lazebnik. "Learning deep structure-preserving image-text embeddings." Proceedings of the IEEE conference on computer vision and pattern recognition. 2016

PDF

Feb, 2019

4

Seongeun Jang

MolGAN: An implicit generative model for small molecular graphs

N. De Cao and T. Kipf. Molgan: An implicit generative model for small molecular graphs. arXiv:1805.11973, 2018.

PDF

Mar, 2019

5

Sunwoo Kim

Iris recognition Towards More Accurate Iris Recognition Using Deeply Learned Spatially Corresponding Features

Z. Zhao and A. Kumar, "Towards More Accurate Iris Recognition Using Deeply Learned Spatially Corresponding Features," 2017 IEEE International Conference on Computer Vision (ICCV), 2017, pp. 3829-3838, doi: 10.1109/ICCV.2017.411.

PDF

Mar, 2019

6

Daeung Kim

Convolutional Neural Networks for Sentence Classification

Y. Kim, Convolutional Neural Networks for Sentence Classification

PDF

Apr, 2019

7

Sanghyuck Na

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

A. Radford, L. Metz, S. Chintala. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

PDF

Apr, 2019

8

Changhoon Jeong

Trust Region Policy Optimization

J. Schulman, S. Levine, P. Moritz, M. I. Jordan, P. Abbeel. Trust Region Policy Optimization

PDF

May, 2019

9

Sanghyun Seo

Networks Dissection
& GAN Dissection

D. Bau, Jun-Yan Zhu, H. Strobelt, B. Zhou, J. B. Tenenbaum, W. T. Freeman, A. Torralba. GAN Dissection: Visualizing and Understanding Generative Adversarial Networks

PDF

May, 2019

10

Park MinKyu

Learning Deep Representations of Fine-Grained Visual Descriptions

S. Reed, Z. Akata, H. Lee, B. Schiele. Learning Deep Representations of Fine-Grained Visual Descriptions

PDF

June, 2019

11

Hyojin Ki

Show, Attend and Tell: Neural Image Caption Generation with visual Attention

Xu, Kelvin, et al. "Show, attend and tell: Neural image caption generation
with visual attention." International conference on machine learning. 2015.
(ICML 2015)

PDF

June, 2019

12

Changhoon Jeong

Playing hard exploration games by watching YouTube

Y. Aytar, T. Pfaff, D. Budden, T. Le Paine, Z. Wang, N. de Freitas. Playing hard exploration games by watching YouTube

PDF

July, 2019

13

Jang SeongEun

Medical Image Segmentation with U-Net

O. Ronneberger, P. Fischer, T. Brox. U-Net: Convolutional Networks for Biomedical Image Segmentation

PDF

July, 2019

14

Sunwoo Kim

Fully-Convolutional Siamese Networks for Object Tracking

L. Bertinetto, J. Valmadre, J. F. Henriques, A. Vedaldi, P. H. S. Torr. Fully-Convolutional Siamese Networks for Object Tracking

PDF

July, 2019

15

Daeung Kim

Character-level Convolutional Networks for Text Classification

X. Zhang, J. Zhao, Y. LeCun. Character-level Convolutional Networks for Text Classification

PDF

Aug, 2019

16

Sanghyuck Na

Semantic Image synthesis with
Spatially-Adaptive Normalization

T. Park, M. Liu, T. Wang, J. Zhu. Semantic Image Synthesis with Spatially-Adaptive Normalization

PDF

Aug, 2019

17

Hyojin Ki

Knowing when to look: Adaptive Attention via A Visual
Sentinel for Image Captioning

Jiasen Lu, Caiming Xiong, Devi Parikh, Richard Socher. Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning

PDF

Aug, 2019

18

Daeung Kim

DeViSE: A Deep Visual-Semantic Embedding Model

A. Frome, G. S. Corrado, J. Shlens, S. Bengio, J. Dean, M. Ranzato, T. Mikolov. DeViSE: A Deep Visual-Semantic Embedding Model

PDF

Sept, 2019

19

Changhoon Jeong

Meta Learning

O. Vinyals et al. Matching Networks for One Shot Learning, Z. Li et al. Meta-SGD: Learning to Learn Quickly for Few-Shot Learning, A. Nichol et al. On First-Order Meta-Learning Algorithms

PDF

Sept, 2019

20

Sanghyuck Na

FIGR : Few-shot Image Generation with Reptile

L. Clouâtre, M. Demers. FIGR: Few-shot Image Generation with Reptile

PDF

Sept, 2019

21

Sunwoo Kim

General semantic Image segmentation & PSAnet for few shot semantic segmentation

K. Wang, J. Hao Liew, Y. Zou, D. Zhou, J. Feng. PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment

PDF

Oct, 2019

22

Sanghyun Seo

Recent Language Models

Vaswani, Ashish, et al. "Attention is all you need." Advances in neural information processing systems. 2017.

PDF

Oct, 2019

23

Park MinKyu

Webly Supervised Learning Meets Zero-shot Learning: A Hybrid Approach for Fine-grained Classification

L. Niu, A. Veeraraghavan, A. Sabharwal. Webly Supervised Learning Meets Zero-shot Learning: A Hybrid Approach for Fine-grained Classification

PDF

Nov, 2019

24

Jang SeongEun

Drug Discovery and
Development

Jaeger, Sabrina, Simone Fulle, and Samo Turk. "Mol2vec: unsupervised machine learning approach with chemical intuition." Journal of chemical information and modeling 58.1 (2018): 27-35.

PDF

Nov, 2019

25

Mehret Abraha

Artificial intellegince and Robot Path Planning

X. Dai, S. Long, Z. Zhang, D. Gong. Mobile Robot Path Planning Based on Ant Colony Algorithm With A* Heuristic Method

PDF

Nov, 2019

26

Changhoon Jeong

Generative Model

I. J. Goodfellow et al. Generative Adversarial Nets, D. P. Kingma et al. Auto-Encoding Variational Bayes

PDF

Dec, 2019

2018 Seminars


No.

Speaker

Title

Reference

Slides

Date

1

Changhoon Jeong

Neural Architecture Search

B. Zoph and Q. V. Le, “Neural architecture search with reinforcement learning,” 2016, arXiv:1611.01578.

PDF

April, 2018

2

Sanghyun Seo

Learning Deep Features for
Discriminative Localization

Lin, Min, Qiang Chen, and Shuicheng Yan. "Network in network." arXiv
preprint arXiv:1312.4400 (2013)

PDF

April, 2018

3

Hyun-Min Park

Pattern Recognition : Bayesian Classifier

Pattern Recognition and Machine Learning, Christopher M. Bishop

PDF

May, 2018

4

Hyun-Min Park

See, Hear, and Read: Deep Aligned Representations

Aytar Y, Vondrick C, Torralba A (2017) See, hear, and read: deep aligned representations. arXiv preprint arXiv:1706.00932

PDF

Nov, 2018

2017 Seminars


No.

Speaker

Title

Reference

Slides

Date

1

Sanghyun Seo

Playing Atari With Deep Reinforcement Learning

Mnih, Volodymyr, et al. “Playing atari with deep reinforcement learning” arXiv preprint arXiv:1312.5602 (2013).

PDF

2017-03-10

2

Jisang Yun

Comparison of word2vec Models Focus on the semantic Segmentation

신수미, 배수영. “의미구분 단위에 따른 word2vec 모델 비교” 한국정보과학회 학술발표논문집,(2016): 753-755.

PDF

2017-03-17

3

Hoonyeob Na

Deep Learning for stock prediction using numerical and textual information

Ryo Akita, Akira Yoshihara, Takashi Matsubara, Kuniaki Uehara “Deep Learning for stock prediction using numerical and textual information” ICIS 2016, June26-20, 2016, Okayama, Japan , 26-29ek

PDF

2017-03-31

4

Arjun Magotra

Learning CNN-LSTM Architectures for Image Caption Generation

Soh, Moses. “Learning CNN-LSTM Architectures for Image Caption Generation.“

PDF

2017-04-07