์ผ | ์ | ํ | ์ | ๋ชฉ | ๊ธ | ํ |
---|---|---|---|---|---|---|
1 | 2 | |||||
3 | 4 | 5 | 6 | 7 | 8 | 9 |
10 | 11 | 12 | 13 | 14 | 15 | 16 |
17 | 18 | 19 | 20 | 21 | 22 | 23 |
24 | 25 | 26 | 27 | 28 | 29 | 30 |
Tags
- SUMBT:Slot-Utterance Matching for Universal and Scalable Belief Tracking
- ์ ๋ณด์ฒ๋ฆฌ๊ธฐ์ฌ์ ๊ณต์ํฉ๊ฒฉํ๊ธฐ
- ์ ๋ณด์ฒ๋ฆฌ๊ธฐ์ฌ ์ฑ ์ถ์ฒ
- ๋ฐ์ดํฐ ํฉ์ฑ
- classification text
- ๊ฒ์์์ง
- How Much Knowledge Can You Pack Into the Parameters of a Language Model?
- ๋ชจ๋์๋ฅ๋ฌ๋
- ๋ฅ๋ฌ๋๊ธฐ์ด
- DST fewshot learning
- ์ ๋ณด์ฒ๋ฆฌ๊ธฐ์ฌ ์์ ๋น
- dialogue state tracking
- fasttext text classification ํ๊ธ
- til
- Zero-shot transfer learning with synthesized data for multi-domain dialogue state tracking
- DST zeroshot learning
- Python
- MySQL
- ํ๋ก๊ทธ๋๋จธ์ค
- ์์ฐ์ด์ฒ๋ฆฌ ๋ ผ๋ฌธ ๋ฆฌ๋ทฐ
- few shot dst
- ํ์ด์ฌ์ ํ์ด์ฌ๋ต๊ฒ
- ๋ค์ด๋๋ฏน ํ๋ก๊ทธ๋๋ฐ
- ์ ๋ณด์ฒ๋ฆฌ๊ธฐ์ฌ์ ๊ณต์
- 2020์ ๋ณด์ฒ๋ฆฌ๊ธฐ์ฌํ๊ธฐ
- Leveraging Slot Descriptions for Zero-Shot Cross-Domain Dialogue State Tracking
- Few Shot Dialogue State Tracking using Meta-learning
- From Machine Reading Comprehension to Dialogue State Tracking: Bridging the Gap
- ๋ฐฑ์ค
- nlp๋ ผ๋ฌธ๋ฆฌ๋ทฐ
Archives
- Today
- Total
๋ชฉ๋ก๋จ์ง๋ฒํธ๋ถ์ด๊ธฐ (1)
๐ฒ์๋ผ๋๋์ฒญ๋
Q 2667 ๋จ์ง๋ฒํธ ๋ถ์ด๊ธฐ JAVA
dfs ๋ฅผ ์ด๋ป๊ฒ ์ฐ๋๊ฑด๊ฐ ๊ณ ๋ฏผํ์๋๋ฐ ๊ตฌ๊ธ๋ง์ ํ๋ค๋ณด๋ dfs๋ฅผ ์๋ ์ ์ ์ ์ด๋ ๊ฒ ๋ค ๋ฐฉํฅ์ผ๋ก ์ฌ์ฉํ๋ ๋ฌธ์ ์ธ ๊ฒ์ ์๊ฒ ๋์๋ค. package graph; import java.util.*; public class Q2667 { static int[][]arr; static int[][]visit; static int[] di = {-1,0,1,0}; static int[] dj = {0 ,-1,0,1}; static int num, cnt; public static void main(String[] args) { Scanner scan =new Scanner(System.in); num = Integer.parseInt(scan.nextLine()); arr = new int[num][num]..
์๊ณ ๋ฆฌ์ฆ ๋ฌธ์ ํ์ด
2019. 5. 7. 11:22