Learning with Deep Cascades. - Giulia DeSalvo; Mehryar Mohri; Umar Syed (ALT, 2015)

Random Composite Forests. - Giulia DeSalvo; Mehryar Mohri (AAAI, 2016)

Learning with Rejection. - Corinna Cortes; Giulia DeSalvo; Mehryar Mohri (ALT, 2016)

Boosting with Abstention. - Corinna Cortes; Giulia DeSalvo; Mehryar Mohri (NIPS, 2016)

Efficient Hyperparameter Optimization and Infinitely Many Armed Bandits. - Lisha Li; Kevin G. Jamieson; Giulia DeSalvo; Afshin Rostamizadeh; Ameet Talwalkar (CoRR, 2016)

Hyperband: Bandit-Based Configuration Evaluation for Hyperparameter Optimization. - Lisha Li; Kevin G. Jamieson; Giulia DeSalvo; Afshin Rostamizadeh; Ameet Talwalkar (ICLR (Poster), 2017)

On-line Learning with Abstention. - Corinna Cortes; Giulia DeSalvo; Mehryar Mohri; Scott Yang (CoRR, 2017)

Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization. - Lisha Li; Kevin G. Jamieson; Giulia DeSalvo; Afshin Rostamizadeh; Ameet Talwalkar (J. Mach. Learn. Res., 2017)

Online Learning with Abstention. - Corinna Cortes; Giulia DeSalvo; Claudio Gentile; Mehryar Mohri; Scott Yang (ICML, 2018)

Region-Based Active Learning. - Corinna Cortes; Giulia DeSalvo; Claudio Gentile; Mehryar Mohri; Ningshan Zhang (AISTATS, 2019)

Online Learning with Sleeping Experts and Feedback Graphs. - Corinna Cortes; Giulia DeSalvo; Claudio Gentile; Mehryar Mohri; Scott Yang (ICML, 2019)

Active Learning with Disagreement Graphs. - Corinna Cortes; Giulia DeSalvo; Mehryar Mohri; Ningshan Zhang; Claudio Gentile (ICML, 2019)

Understanding the Effects of Batching in Online Active Learning. - Kareem Amin 002; Corinna Cortes; Giulia DeSalvo; Afshin Rostamizadeh (AISTATS, 2020)

Adaptive Region-Based Active Learning. - Corinna Cortes; Giulia DeSalvo; Claudio Gentile; Mehryar Mohri; Ningshan Zhang (ICML, 2020)

Online Learning with Dependent Stochastic Feedback Graphs. - Corinna Cortes; Giulia DeSalvo; Claudio Gentile; Mehryar Mohri; Ningshan Zhang (ICML, 2020)

Learning with Labeling Induced Abstentions. - Kareem Amin 002; Giulia DeSalvo; Afshin Rostamizadeh (NeurIPS, 2021)

Batch Active Learning at Scale. - Gui Citovsky; Giulia DeSalvo; Claudio Gentile; Lazaros Karydas; Anand Rajagopalan; Afshin Rostamizadeh; Sanjiv Kumar (NeurIPS, 2021)

Online Active Learning with Surrogate Loss Functions. - Giulia DeSalvo; Claudio Gentile; Tobias Sommer Thune (NeurIPS, 2021)

Firebolt: Weak Supervision Under Weaker Assumptions. - Zhaobin Kuang; Chidubem G. Arachie; Bangyong Liang; Pradyumna Narayana; Giulia DeSalvo; Michael S. Quinn; Bert Huang; Geoffrey Downs; Yang Yang (AISTATS, 2022)

Agile Modeling: From Concept to Classifier in Minutes. - Otilia Stretcu; Edward Vendrow; Kenji Hata; Krishnamurthy Viswanathan; Vittorio Ferrari; Sasan Tavakkol; Wenlei Zhou; Aditya Avinash; Enming Luo; Neil Gordon Alldrin; MohammadHossein Bateni; Gabriel Berger; et al. (ICCV, 2023)

Leveraging Importance Weights in Subset Selection. - Gui Citovsky; Giulia DeSalvo; Sanjiv Kumar; Srikumar Ramalingam; Afshin Rostamizadeh; Yunjuan Wang (ICLR, 2023)

Two-Step Active Learning for Instance Segmentation with Uncertainty and Diversity Sampling. - Ke Yu; Stephen Albro; Giulia DeSalvo; Suraj Kothawade; Abdullah Rashwan; Sasan Tavakkol; Kayhan Batmanghelich; Xiaoqi Yin (CoRR, 2023)

SpacTor-T5: Pre-training T5 Models with Span Corruption and Replaced Token Detection. - Ke Ye; Heinrich Jiang; Afshin Rostamizadeh; Ayan Chakrabarti; Giulia DeSalvo; Jean-François Kagy; Lazaros Karydas; Gui Citovsky; Sanjiv Kumar (CoRR, 2024)

GIST: Greedy Independent Set Thresholding for Diverse Data Summarization. - Matthew Fahrbach; Srikumar Ramalingam; Morteza Zadimoghaddam; Sara Ahmadian; Gui Citovsky; Giulia DeSalvo (CoRR, 2024)

No more hard prompts: SoftSRV prompting for synthetic data generation. - Giulia DeSalvo; Jean-François Kagy; Lazaros Karydas; Afshin Rostamizadeh; Sanjiv Kumar (CoRR, 2024)

Theory and algorithms for learning with rejection in binary classification. - Corinna Cortes; Giulia DeSalvo; Mehryar Mohri (Ann. Math. Artif. Intell., 2024)