Online multiclass boosting. - Young Hun Jung; Jack Goetz; Ambuj Tewari (NIPS, 2017)

Online Multiclass Boosting. - Young Hun Jung; Ambuj Tewari (CoRR, 2017)

Online Boosting Algorithms for Multi-label Ranking. - Young Hun Jung; Ambuj Tewari (AISTATS, 2018)

Online Multiclass Boosting with Bandit Feedback. - Daniel T. Zhang; Young Hun Jung; Ambuj Tewari (AISTATS, 2019)

Online Learning via the Differential Privacy Lens. - Jacob D. Abernethy; Young Hun Jung; Chansoo Lee; Audra McMillan; Ambuj Tewari (NeurIPS, 2019)

Regret Bounds for Thompson Sampling in Episodic Restless Bandit Problems. - Young Hun Jung; Ambuj Tewari (NeurIPS, 2019)

Regret Bounds for Thompson Sampling in Restless Bandit Problems. - Young Hun Jung; Ambuj Tewari (CoRR, 2019)

Thompson Sampling in Non-Episodic Restless Bandits. - Young Hun Jung; Marc Abeille; Ambuj Tewari (CoRR, 2019)

Online Boosting for Multilabel Ranking with Top-k Feedback. - Daniel T. Zhang; Young Hun Jung; Ambuj Tewari (CoRR, 2019)

On the Equivalence between Online and Private Learnability beyond Binary Classification. - Young Hun Jung; Baekjin Kim; Ambuj Tewari (NeurIPS, 2020)

Offline RL With Resource Constrained Online Deployment. - Jayanth Reddy Regatti; Aniket Anand Deshmukh; Frank Cheng; Young Hun Jung; Abhishek Gupta 002; Ürün Dogan (CoRR, 2021)

Masked LARk: Masked Learning, Aggregation and Reporting worKflow. - Joseph J. Pfeiffer III; Denis Charles; Davis Gilton; Young Hun Jung; Mehul Parsana; Erik Anderson (CoRR, 2021)