Selected Papers

1. XGBoost: A Scalable Tree Boosting System, Tianqi Chen and Carlos Guestrin (PDF)

2. Stochastic gradient boosting, Jerome H. Friedman (PDF)

3. Experiments with a New Boosting Algorithm, Yoav Freund and Robert E. Schapire (PDF)

4. An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants, Eric Bauer and Ron Kohavi (PDF)

5. ImageNet Classification with Deep Convolutional Neural Networks, Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton (PDF)

6. Probabilistic Matrix Factorization for Automated Machine Learning, Nicolo Fusi, Rishit Sheth (PDF)

7. QnAMaker: Data to Bot in 2 Minutes, Parag Agrawal, Tulasi Menon, Aya Kamel, Michel Naim, Chaikesh Chouragade, Gurvinder Singh, Rohan Kulkarni, Anshuman Suri, Sahithi Katakam, Vineet Pratik, Prakul Bansal, Simerpreet Kaur, Neha Rajput, Anand Duggal, Achraf Chalabi, Prashant Choudhari, Reddy Satti, Niranjan Nayak (PDF)

8. Learning Bidirectional Intent Embeddings by Convolutional Deep Structured Semantic Models for Spoken Language Understanding, Yun-Nung Chen, Dilek Z. Hakkani-Tur, Xiaodong He (PDF)