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Alexandru Niculescu-Mizil
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2020 – today
- 2021
- [c25]Honglu Zhou, Asim Kadav, Farley Lai, Alexandru Niculescu-Mizil, Martin Renqiang Min, Mubbasir Kapadia, Hans Peter Graf:
Hopper: Multi-hop Transformer for Spatiotemporal Reasoning. ICLR 2021 - [i4]Honglu Zhou, Asim Kadav, Farley Lai, Alexandru Niculescu-Mizil, Martin Renqiang Min, Mubbasir Kapadia, Hans Peter Graf:
Hopper: Multi-hop Transformer for Spatiotemporal Reasoning. CoRR abs/2103.10574 (2021) - 2020
- [i3]Shuchu Han, Alexandru Niculescu-Mizil:
Supervised Feature Subset Selection and Feature Ranking for Multivariate Time Series without Feature Extraction. CoRR abs/2005.00259 (2020)
2010 – 2019
- 2017
- [c24]Alexandru Niculescu-Mizil, Ehsan Abbasnejad:
Label Filters for Large Scale Multilabel Classification. AISTATS 2017: 1448-1457 - [c23]Adarsh Prasad, Alexandru Niculescu-Mizil, Pradeep Ravikumar:
On Separability of Loss Functions, and Revisiting Discriminative Vs Generative Models. NIPS 2017: 7050-7059 - 2014
- [j4]Abhishek B. Sharma, Franjo Ivancic, Alexandru Niculescu-Mizil, Haifeng Chen, Guofei Jiang:
Modeling and analytics for cyber-physical systems in the age of big data. SIGMETRICS Perform. Evaluation Rev. 41(4): 74-77 (2014) - [c22]Anelia Angelova, Alexandru Niculescu-Mizil:
Feature combination with Multi-Kernel Learning for fine-grained visual classification. WACV 2014: 241-246 - 2013
- [c21]Chris Paxton, Suchi Saria, Alexandru Niculescu-Mizil:
Developing Predictive Models Using Electronic Medical Records: Challenges and Pitfalls. AMIA 2013 - [i2]Diane Oyen, Alexandru Niculescu-Mizil, Rachel Ostroff, Alex Stewart, Vincent P. Clark:
Controlling the Precision-Recall Tradeoff in Differential Dependency Network Analysis. CoRR abs/1307.2611 (2013) - 2012
- [c20]Abhishek Kumar, Alexandru Niculescu-Mizil, Koray Kavukcuoglu, Hal Daumé III:
A Binary Classification Framework for Two-Stage Multiple Kernel Learning. ICML 2012 - [c19]Siddharth Gopal, Yiming Yang, Bing Bai, Alexandru Niculescu-Mizil:
Bayesian models for Large-scale Hierarchical Classification. NIPS 2012: 2420-2428 - [c18]Alexandru Niculescu-Mizil, Rich Caruana:
Inductive Transfer for Bayesian Network Structure Learning. ICML Unsupervised and Transfer Learning 2012: 167-180 - [i1]Alexandru Niculescu-Mizil, Rich Caruana:
Obtaining Calibrated Probabilities from Boosting. CoRR abs/1207.1403 (2012) - 2011
- [j3]Yan Liu, Alexandru Niculescu-Mizil, Aurélie C. Lozano, Yong Lu:
Temporal Graphical Models for Cross-Species Gene Regulatory Network Discovery. J. Bioinform. Comput. Biol. 9(2): 231-250 (2011) - 2010
- [j2]Robert Kleinberg
, Alexandru Niculescu-Mizil, Yogeshwer Sharma:
Regret bounds for sleeping experts and bandits. Mach. Learn. 80(2-3): 245-272 (2010) - [c17]Yan Liu, Alexandru Niculescu-Mizil, Aurélie C. Lozano, Yong Lu:
Learning Temporal Causal Graphs for Relational Time-Series Analysis. ICML 2010: 687-694
2000 – 2009
- 2009
- [c16]Yan Liu, Alexandru Niculescu-Mizil, Wojciech Gryc:
Topic-link LDA: joint models of topic and author community. ICML 2009: 665-672 - [c15]Aurélie C. Lozano, Hongfei Li, Alexandru Niculescu-Mizil, Yan Liu, Claudia Perlich, Jonathan R. M. Hosking, Naoki Abe:
Spatial-temporal causal modeling for climate change attribution. KDD 2009: 587-596 - [c14]Alexandru Niculescu-Mizil, Claudia Perlich, Grzegorz Swirszcz, Vikas Sindhwani, Yan Liu, Prem Melville, Dong Wang, Jing Xiao, Jianying Hu, Moninder Singh, Wei Xiong Shang, Yanfeng Zhu:
Winning the KDD Cup Orange Challenge with Ensemble Selection. KDD Cup 2009: 23-34 - 2008
- [b1]Alexandru Niculescu-Mizil:
Getting the Most out of your Data: Multitask Bayesian Network Structure Learning, Predicting Good Probabilities and Ensemble Selection. Cornell University, USA, 2008 - [c13]Robert D. Kleinberg, Alexandru Niculescu-Mizil, Yogeshwer Sharma:
Regret Bounds for Sleeping Experts and Bandits. COLT 2008: 425-436 - 2007
- [j1]Tom Fawcett
, Alexandru Niculescu-Mizil:
PAV and the ROC convex hull. Mach. Learn. 68(1): 97-106 (2007) - [c12]Mark Schmidt, Alexandru Niculescu-Mizil, Kevin P. Murphy:
Learning Graphical Model Structure Using L1-Regularization Paths. AAAI 2007: 1278-1283 - [c11]David B. Skalak, Alexandru Niculescu-Mizil, Rich Caruana:
Classifier Loss Under Metric Uncertainty. ECML 2007: 310-322 - [c10]Alexandru Niculescu-Mizil, Rich Caruana:
Inductive Transfer for Bayesian Network Structure Learning. AISTATS 2007: 339-346 - 2006
- [c9]Rich Caruana, Art Munson, Alexandru Niculescu-Mizil:
Getting the Most Out of Ensemble Selection. ICDM 2006: 828-833 - [c8]Rich Caruana, Alexandru Niculescu-Mizil:
An empirical comparison of supervised learning algorithms. ICML 2006: 161-168 - [c7]Cristian Bucila, Rich Caruana, Alexandru Niculescu-Mizil:
Model compression. KDD 2006: 535-541 - 2005
- [c6]Alexandru Niculescu-Mizil, Rich Caruana:
Predicting good probabilities with supervised learning. ICML 2005: 625-632 - [c5]Alexandru Niculescu-Mizil, Rich Caruana:
Obtaining Calibrated Probabilities from Boosting. UAI 2005: 413- - 2004
- [c4]Rich Caruana, Alexandru Niculescu-Mizil, Geoff Crew, Alex Ksikes:
Ensemble selection from libraries of models. ICML 2004 - [c3]Rich Caruana, Alexandru Niculescu-Mizil:
Data mining in metric space: an empirical analysis of supervised learning performance criteria. KDD 2004: 69-78 - [c2]Rich Caruana, Alexandru Niculescu-Mizil:
An Empirical Evaluation of Supervised Learning for ROC Area. ROCAI 2004: 1-8 - [c1]Rich Caruana, Alexandru Niculescu-Mizil:
Data Mining in Metric Space: An Empirical Analysis of Supervised Learning Performance Criteria. ROCAI 2004: 9-18
Coauthor Index
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