Zobrazeno 1 - 10
of 2 417
pro vyhledávání: '"Kim Kyung-Min"'
In reinforcement learning, off-policy actor-critic approaches like DDPG and TD3 are based on the deterministic policy gradient. Herein, the Q-function is trained from off-policy environment data and the actor (policy) is trained to maximize the Q-fun
Externí odkaz:
http://arxiv.org/abs/2410.11833
Collaborative filtering (CF) remains essential in recommender systems, leveraging user--item interactions to provide personalized recommendations. Meanwhile, a number of CF techniques have evolved into sophisticated model architectures based on multi
Externí odkaz:
http://arxiv.org/abs/2409.05878
Autor:
Yoo, Kang Min, Han, Jaegeun, In, Sookyo, Jeon, Heewon, Jeong, Jisu, Kang, Jaewook, Kim, Hyunwook, Kim, Kyung-Min, Kim, Munhyong, Kim, Sungju, Kwak, Donghyun, Kwak, Hanock, Kwon, Se Jung, Lee, Bado, Lee, Dongsoo, Lee, Gichang, Lee, Jooho, Park, Baeseong, Shin, Seongjin, Yu, Joonsang, Baek, Seolki, Byeon, Sumin, Cho, Eungsup, Choe, Dooseok, Han, Jeesung, Jin, Youngkyun, Jun, Hyein, Jung, Jaeseung, Kim, Chanwoong, Kim, Jinhong, Kim, Jinuk, Lee, Dokyeong, Park, Dongwook, Sohn, Jeong Min, Han, Sujung, Heo, Jiae, Hong, Sungju, Jeon, Mina, Jung, Hyunhoon, Jung, Jungeun, Jung, Wangkyo, Kim, Chungjoon, Kim, Hyeri, Kim, Jonghyun, Kim, Min Young, Lee, Soeun, Park, Joonhee, Shin, Jieun, Yang, Sojin, Yoon, Jungsoon, Lee, Hwaran, Bae, Sanghwan, Cha, Jeehwan, Gylleus, Karl, Ham, Donghoon, Hong, Mihak, Hong, Youngki, Hong, Yunki, Jang, Dahyun, Jeon, Hyojun, Jeon, Yujin, Jeong, Yeji, Ji, Myunggeun, Jin, Yeguk, Jo, Chansong, Joo, Shinyoung, Jung, Seunghwan, Kim, Adrian Jungmyung, Kim, Byoung Hoon, Kim, Hyomin, Kim, Jungwhan, Kim, Minkyoung, Kim, Minseung, Kim, Sungdong, Kim, Yonghee, Kim, Youngjun, Kim, Youngkwan, Ko, Donghyeon, Lee, Dughyun, Lee, Ha Young, Lee, Jaehong, Lee, Jieun, Lee, Jonghyun, Lee, Jongjin, Lee, Min Young, Lee, Yehbin, Min, Taehong, Min, Yuri, Moon, Kiyoon, Oh, Hyangnam, Park, Jaesun, Park, Kyuyon, Park, Younghun, Seo, Hanbae, Seo, Seunghyun, Sim, Mihyun, Son, Gyubin, Yeo, Matt, Yeom, Kyung Hoon, Yoo, Wonjoon, You, Myungin, Ahn, Doheon, Ahn, Homin, Ahn, Joohee, Ahn, Seongmin, An, Chanwoo, An, Hyeryun, An, Junho, An, Sang-Min, Byun, Boram, Byun, Eunbin, Cha, Jongho, Chang, Minji, Chang, Seunggyu, Cho, Haesong, Cho, Youngdo, Choi, Dalnim, Choi, Daseul, Choi, Hyoseok, Choi, Minseong, Choi, Sangho, Choi, Seongjae, Choi, Wooyong, Chun, Sewhan, Go, Dong Young, Ham, Chiheon, Han, Danbi, Han, Jaemin, Hong, Moonyoung, Hong, Sung Bum, Hwang, Dong-Hyun, Hwang, Seongchan, Im, Jinbae, Jang, Hyuk Jin, Jang, Jaehyung, Jang, Jaeni, Jang, Sihyeon, Jang, Sungwon, Jeon, Joonha, Jeong, Daun, Jeong, Joonhyun, Jeong, Kyeongseok, Jeong, Mini, Jin, Sol, Jo, Hanbyeol, Jo, Hanju, Jo, Minjung, Jung, Chaeyoon, Jung, Hyungsik, Jung, Jaeuk, Jung, Ju Hwan, Jung, Kwangsun, Jung, Seungjae, Ka, Soonwon, Kang, Donghan, Kang, Soyoung, Kil, Taeho, Kim, Areum, Kim, Beomyoung, Kim, Byeongwook, Kim, Daehee, Kim, Dong-Gyun, Kim, Donggook, Kim, Donghyun, Kim, Euna, Kim, Eunchul, Kim, Geewook, Kim, Gyu Ri, Kim, Hanbyul, Kim, Heesu, Kim, Isaac, Kim, Jeonghoon, Kim, Jihye, Kim, Joonghoon, Kim, Minjae, Kim, Minsub, Kim, Pil Hwan, Kim, Sammy, Kim, Seokhun, Kim, Seonghyeon, Kim, Soojin, Kim, Soong, Kim, Soyoon, Kim, Sunyoung, Kim, Taeho, Kim, Wonho, Kim, Yoonsik, Kim, You Jin, Kim, Yuri, Kwon, Beomseok, Kwon, Ohsung, Kwon, Yoo-Hwan, Lee, Anna, Lee, Byungwook, Lee, Changho, Lee, Daun, Lee, Dongjae, Lee, Ha-Ram, Lee, Hodong, Lee, Hwiyeong, Lee, Hyunmi, Lee, Injae, Lee, Jaeung, Lee, Jeongsang, Lee, Jisoo, Lee, Jongsoo, Lee, Joongjae, Lee, Juhan, Lee, Jung Hyun, Lee, Junghoon, Lee, Junwoo, Lee, Se Yun, Lee, Sujin, Lee, Sungjae, Lee, Sungwoo, Lee, Wonjae, Lee, Zoo Hyun, Lim, Jong Kun, Lim, Kun, Lim, Taemin, Na, Nuri, Nam, Jeongyeon, Nam, Kyeong-Min, Noh, Yeonseog, Oh, Biro, Oh, Jung-Sik, Oh, Solgil, Oh, Yeontaek, Park, Boyoun, Park, Cheonbok, Park, Dongju, Park, Hyeonjin, Park, Hyun Tae, Park, Hyunjung, Park, Jihye, Park, Jooseok, Park, Junghwan, Park, Jungsoo, Park, Miru, Park, Sang Hee, Park, Seunghyun, Park, Soyoung, Park, Taerim, Park, Wonkyeong, Ryu, Hyunjoon, Ryu, Jeonghun, Ryu, Nahyeon, Seo, Soonshin, Seo, Suk Min, Shim, Yoonjeong, Shin, Kyuyong, Shin, Wonkwang, Sim, Hyun, Sim, Woongseob, Soh, Hyejin, Son, Bokyong, Son, Hyunjun, Son, Seulah, Song, Chi-Yun, Song, Chiyoung, Song, Ka Yeon, Song, Minchul, Song, Seungmin, Wang, Jisung, Yeo, Yonggoo, Yi, Myeong Yeon, Yim, Moon Bin, Yoo, Taehwan, Yoo, Youngjoon, Yoon, Sungmin, Yoon, Young Jin, Yu, Hangyeol, Yu, Ui Seon, Zuo, Xingdong, Bae, Jeongin, Bae, Joungeun, Cho, Hyunsoo, Cho, Seonghyun, Cho, Yongjin, Choi, Taekyoon, Choi, Yera, Chung, Jiwan, Han, Zhenghui, Heo, Byeongho, Hong, Euisuk, Hwang, Taebaek, Im, Seonyeol, Jegal, Sumin, Jeon, Sumin, Jeong, Yelim, Jeong, Yonghyun, Jiang, Can, Jiang, Juyong, Jin, Jiho, Jo, Ara, Jo, Younghyun, Jung, Hoyoun, Jung, Juyoung, Kang, Seunghyeong, Kim, Dae Hee, Kim, Ginam, Kim, Hangyeol, Kim, Heeseung, Kim, Hyojin, Kim, Hyojun, Kim, Hyun-Ah, Kim, Jeehye, Kim, Jin-Hwa, Kim, Jiseon, Kim, Jonghak, Kim, Jung Yoon, Kim, Rak Yeong, Kim, Seongjin, Kim, Seoyoon, Kim, Sewon, Kim, Sooyoung, Kim, Sukyoung, Kim, Taeyong, Ko, Naeun, Koo, Bonseung, Kwak, Heeyoung, Kwon, Haena, Kwon, Youngjin, Lee, Boram, Lee, Bruce W., Lee, Dagyeong, Lee, Erin, Lee, Euijin, Lee, Ha Gyeong, Lee, Hyojin, Lee, Hyunjeong, Lee, Jeeyoon, Lee, Jeonghyun, Lee, Jongheok, Lee, Joonhyung, Lee, Junhyuk, Lee, Mingu, Lee, Nayeon, Lee, Sangkyu, Lee, Se Young, Lee, Seulgi, Lee, Seung Jin, Lee, Suhyeon, Lee, Yeonjae, Lee, Yesol, Lee, Youngbeom, Lee, Yujin, Li, Shaodong, Liu, Tianyu, Moon, Seong-Eun, Moon, Taehong, Nihlenramstroem, Max-Lasse, Oh, Wonseok, Oh, Yuri, Park, Hongbeen, Park, Hyekyung, Park, Jaeho, Park, Nohil, Park, Sangjin, Ryu, Jiwon, Ryu, Miru, Ryu, Simo, Seo, Ahreum, Seo, Hee, Seo, Kangdeok, Shin, Jamin, Shin, Seungyoun, Sin, Heetae, Wang, Jiangping, Wang, Lei, Xiang, Ning, Xiao, Longxiang, Xu, Jing, Yi, Seonyeong, Yoo, Haanju, Yoo, Haneul, Yoo, Hwanhee, Yu, Liang, Yu, Youngjae, Yuan, Weijie, Zeng, Bo, Zhou, Qian, Cho, Kyunghyun, Ha, Jung-Woo, Park, Joonsuk, Hwang, Jihyun, Kwon, Hyoung Jo, Kwon, Soonyong, Lee, Jungyeon, Lee, Seungho, Lim, Seonghyeon, Noh, Hyunkyung, Choi, Seungho, Lee, Sang-Woo, Lim, Jung Hwa, Sung, Nako
We introduce HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture, along with competitive capabilities in English, math, and coding. HyperCLOVA X was trained on a balanced mix of Korean, English, and code
Externí odkaz:
http://arxiv.org/abs/2404.01954
Time series forecasting is one of the most essential and ubiquitous tasks in many business problems, including demand forecasting and logistics optimization. Traditional time series forecasting methods, however, have resulted in small models with lim
Externí odkaz:
http://arxiv.org/abs/2402.19402
Preference-based reinforcement learning (PbRL) is an approach that enables RL agents to learn from preference, which is particularly useful when formulating a reward function is challenging. Existing PbRL methods generally involve a two-step procedur
Externí odkaz:
http://arxiv.org/abs/2301.12842
Autor:
Kim, Kyung-Min1 (AUTHOR) kymkim@kcl.re.kr, Park, Sung-Woo1 (AUTHOR), Song, Bhum-Keun2 (AUTHOR), Yoon, Seon-Hee3 (AUTHOR)
Publikováno v:
Polymers (20734360). Oct2024, Vol. 16 Issue 19, p2690. 20p.
Autor:
Shin, Kyuyong, Kwak, Hanock, Kim, Wonjae, Jeong, Jisu, Jung, Seungjae, Kim, Kyung-Min, Ha, Jung-Woo, Lee, Sang-Woo
Recent studies have proposed unified user modeling frameworks that leverage user behavior data from various applications. Many of them benefit from utilizing users' behavior sequences as plain texts, representing rich information in any domain or sys
Externí odkaz:
http://arxiv.org/abs/2212.03760
As online merchandise become more common, many studies focus on embedding-based methods where queries and products are represented in the semantic space. These methods alleviate the problem of vocab mismatch between the language of queries and produc
Externí odkaz:
http://arxiv.org/abs/2207.02516
Autor:
Park, Jinyoung, Yun, Seongjun, Park, Hyeonjin, Kang, Jaewoo, Jeong, Jisu, Kim, Kyung-Min, Ha, Jung-woo, Kim, Hyunwoo J.
Transformer-based models have recently shown success in representation learning on graph-structured data beyond natural language processing and computer vision. However, the success is limited to small-scale graphs due to the drawbacks of full dot-pr
Externí odkaz:
http://arxiv.org/abs/2206.14337
Time series models aim for accurate predictions of the future given the past, where the forecasts are used for important downstream tasks like business decision making. In practice, deep learning based time series models come in many forms, but at a
Externí odkaz:
http://arxiv.org/abs/2205.15894