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Machine Learning and Learning Theory
| Conference | Long Paper | Short Paper |
|---|---|---|
| ICLR’22 | 32.9% (1095/3328) (54 orals, 176 spotlights and 865 posters) | – |
| COLT’14 | 32.1% (45/140) | – |
| COLT’15 | 34.8% (62/178) | – |
| COLT’16 | 26.1% (53/203) | – |
Acceptance Rate of AI Conferences
| Conference | Long Paper | Short Paper |
|---|---|---|
| ACL’14 | 26.2% (146/572) | 26.1% (139/551) |
| ACL’15 | 25.0% (173/692) | 22.4% (145/648) |
| ACL’16 | 28.0% (231/825) | 21.0% (97/463) |
| ACL’17 | 25.0% (195/751) | 18.9% (107/567) |
| ACL’18 | 25.3% (258/1018) | 24.0% (126/526) |
| EMNLP’14 | 30.4% (155/510) | 27.8% (70/252) |
| EMNLP’15 | 26.2% (157/600) | 22.1% (155/700) |
| EMNLP’16 | 25.8% (177/687) | 21.8% (87/400) |
| EMNLP’17 | 25.8% (216/836) | 18.4% (107/582) |
| EMNLP’18 | 25.5% (351/1376) | 23.2% (198/855) |
| NAACL HLT’13 | 30.0% (88/293) | 32.1% (51/162) |
| NAACL HLT’15 | 29.1% (117/402) | 22.1% (69/312) |
| NAACL HLT’16 | 25.3% (100/396) | 28.9% (82/284) |
| NAACL HLT’18 | 32.0% (207/647) | 29.4% (125/425) |
| EACL’12 | 26.0% (85/326) | – |
| EACL’14 | 24.6% (78/317) | 23.1% (46/199) |
| EACL’17 | 27.0% (119/441) | 23.9% (120/502) |
| COLING’12 | 27% (311/1000+) | – |
| COLING’14 | 30.8% (217/705) | – |
| COLING’16 | 32.4% (337/1039) | – |
| COLING’18 | 37.4% (332/888) | – |
| CVPR’14 | 29.9% (540/1807) (104 orals and 436 posters) | – |
| CVPR’15 | 28.3% (602/2123) (71 orals and 531 posters) | – |
| CVPR’16 | 29.9% (643/2145) (83 orals, 123 spotlights and 437 posters) | – |
| CVPR’17 | 29.9% (783/2620) (71 orals, 144 spotlights and 568 posters) | – |
| CVPR’18 | 29.6% (979/3303) (70 orals, 244 spotlights and 685 posters) | – |
| ICCV’13 | 27.9% (454/1629) (41 orals and 413 posters) | – |
| ICCV’15 | 30.9% (525/1698) | – |
| ICCV’17 | 29.0% (621/2143) (45 orals, 56 spotlights and 520 posters) | – |
| ECCV’14 | 27.9% (363/1444) (38 orals and 325 posters) | – |
| ECCV’16 | 26.6% (415/1561) (28 orals, 45 spotlights, and 342 posters) | – |
| ECCV’18 | 31.8% (776/2439) (59 orals and 717 posters) | – |
| ICML’14 | 15.0% (Cycle I), 22.0% (Cycle II) | – |
| ICML’15 | 26.0% (270/1037) | – |
| ICML’16 | 24.0% (322/?) | – |
| ICML’17 | 25.9% (434/1676) | – |
| ICML’18 | 25.1% (621/2473) | – |
| NIPS’14 | 24.7% (414/1678) | – |
| NIPS’15 | 21.9% (403/1838) | – |
| NIPS’16 | 23.6% (569/2403) | – |
| NIPS’17 | 20.9% (678/3240) (40 orals, 112 spotlights and 526 posters) | – |
| NIPS’18 | 20.8% (1011/4856) (30 orals, 168 spotlights and 813 posters) | – |
| ICLR’14 | – | – |
| ICLR’15 | – | – |
| ICLR’16 | – | – |
| ICLR’17 | 39.1% (198/507) (15 orals and 183 posters) | – |
| ICLR’18 | 32.0% (314/981) (23 orals and 291 posters) | – |
| ICLR’19 | 31.4% (500/1591) (24 orals and 476 posters) | – |
| COLT’14 | 32.1% (45/140) | – |
| COLT’15 | 34.8% (62/178) | – |
| COLT’16 | 26.1% (53/203) | – |
| COLT’17 | 32.5% (74/228) | – |
| COLT’18 | 27.2% (91/335) | – |
| UAI’14 | 32.0% (94/292) | – |
| UAI’15 | 34.0% (99/291) | – |
| UAI’16 | 31.0% (85/275) | – |
| UAI’17 | 31.0% (87/282) | – |
| AISTATS’14 | 35.8% (120/335) | – |
| AISTATS’15 | 28.7% (127/442) | – |
| AISTATS’16 | 30.7% (165/537) | – |
| AISTATS’17 | 31.7% (167/?) | – |
| AISTATS’18 | ? | – |
| AAAI’14 | 28.0% | – |
| AAAI’15 | 26.7% (531/1991) | – |
| AAAI’16 | 25.8% (549/2132) | – |
| AAAI’17 | 24.6% (638/2590) | – |
| AAAI’18 | 24.6% (933/3800) | – |
| AAAI’19 | 16.2% (1150/7095) | – |
| IJCAI’13 | 28.0% (413/1473) | – |
| IJCAI’15 | 28.6% (572/1996) | – |
| IJCAI’16 | 24.0% (551/2294) | – |
| IJCAI’17 | 26.0% (660/2540) | – |
| IJCAI’18 | 20.5% (710/3470) | – |
| KDD’14 | 14.6% (151/1036) | – |
| KDD’15 | 19.5% (160/819) | – |
| KDD’16 | 13.7% (142/1115) | – |
| KDD’17 | 17.4% (130/748) | – |
| KDD’18 | 18.4% (181/983) | – |
| SIGIR’14 | 21.0% (82/387) | 40.0% (104/263) |
| SIGIR’15 | 20.0% (70/351) | ? (79/?) |
| SIGIR’16 | 18.0% (62/341) | 30.6% (104/339) |
| SIGIR’17 | 22.0% (78/362) | 30.0% (121/398) |
| SIGIR’18 | 21.0% (86/409) | 30.0% (98/327) |
| WWW’14 | 13.0% (84/645) | – |
| WWW’15 | 14.0% (131/929) | – |
| WWW’16 | 16.0% (115/727) | – |
| WWW’17 | 17.0% (164/966) | – |
| WWW’18 | 15.0% (171/1140) | – |
| WWW’19 | – | – |
| ICDM’14 | 9.77% (71/727) | 9.76% (71/727) |
| ICDM’15 | 8.4% (68/807) | 9.7% (78/807) |
| ICDM’16 | 8.6% (78/904) | 11.0% (100/904) |
| ICDM’17 | 9.3% (72/778) | 10.7% (83/778) |
| ICDM’18 | 8.9% (84/948) | 11.1% (105/948) |
| WSDM’14 | 18.0% (64/355) | – |
| WSDM’15 | 16.4% (39/238) | – |
| WSDM’16 | 18.2% (67/368) | – |
| WSDM’17 | 15.8% (80/505) | – |
| WSDM’18 | 16.1% (84/514) | – |
| WSDM’19 | 16.4% (84/511) | – |
| CIKM’14 | 21.0% (175/838) | – |
| CIKM’15 | 26.0% (165/846) | – |
| CIKM’16 | 23.0% (160/701) | – |
| CIKM’17 | 20.0% (171/855) | – |
| CIKM’18 | 17.0% (147/862) | – |
| SDM’14 | 29.0% (120/389) | – |
| SDM’15 | 22.0% | – |
| SDM’16 | 25.9% | – |
| SDM’17 | 26.0% | – |
| SDM’18 | 23.2% | – |
| INTERSPEECH’14 | – | – |
| INTERSPEECH’15 | 51.0% (~743/1458) | – |
| INTERSPEECH’16 | 50.5% (779/1541) | – |
| INTERSPEECH’17 | 52.0% (799/1582) | – |
| INTERSPEECH’18 | 54.0% (749/?) | – |
| ICASSP’14 | 48.0% (1709/3500) | – |
| ICASSP’15 | 52.0% (?/?) | – |
| ICASSP’16 | 47.0% (1265/2682) | – |
| ICASSP’17 | 52.0% (1220/2518) | – |
| ICASSP’18 | 49.7% (1406/2929) | – |
| ICASSP’19 | – | – |
Recall that only papers from the research track are counted for KDD and WWW (now known as the Web Conference). Short and long paper submissions for ICDM are accepted during the same session, and the paper type is determined by the quality of each submission. Please enable JavaScript to view the.
Research Conference ICML drops their acceptance rate | Area Chairs instructed to be more picky
FAQ
Is Icassp a top conference?
Nevertheless, the top conferences for speech/audio applications are ICASSP and Interspeech.
Is Icml top conference?
One of the top conferences for machine learning is the International Conference on Machine Learning (ICML).