High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups. - Paul Rolland; Jonathan Scarlett; Ilija Bogunovic; Volkan Cevher (AISTATS, 2018)

Mirrored Langevin Dynamics. - Ya-Ping Hsieh; Ali Kavis; Paul Rolland; Volkan Cevher (NeurIPS, 2018)

Efficient learning of smooth probability functions from Bernoulli tests with guarantees. - Paul Rolland; Ali Kavis; Adish Singla; Volkan Cevher (CoRR, 2018)

Efficient learning of smooth probability functions from Bernoulli tests with guarantees. - Paul Rolland; Ali Kavis; Alexander Immer; Adish Singla; Volkan Cevher (ICML, 2019)

Lipschitz constant estimation of Neural Networks via sparse polynomial optimization. - Fabian Latorre; Paul Rolland; Volkan Cevher (ICLR, 2020)

Efficient Proximal Mapping of the 1-path-norm of Shallow Networks. - Fabian Latorre; Paul Rolland; Nadav Hallak; Volkan Cevher (ICML, 2020)

Double-Loop Unadjusted Langevin Algorithm. - Paul Rolland; Armin Eftekhari; Ali Kavis; Volkan Cevher (ICML, 2020)

Robust Reinforcement Learning via Adversarial training with Langevin Dynamics. - Parameswaran Kamalaruban; Yu-Ting Huang 003; Ya-Ping Hsieh; Paul Rolland; Cheng Shi; Volkan Cevher (NeurIPS, 2020)

The Effect of the Intrinsic Dimension on the Generalization of Quadratic Classifiers. - Fabian Latorre; Leello Tadesse Dadi; Paul Rolland; Volkan Cevher (NeurIPS, 2021)

Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models. - Paul Rolland; Volkan Cevher; Matthäus Kleindessner; Chris Russell 001; Dominik Janzing; Bernhard Schölkopf; Francesco Locatello (ICML, 2022)

Identifiability and generalizability from multiple experts in Inverse Reinforcement Learning. - Paul Rolland; Luca Viano; Norman Schürhoff; Boris Nikolov; Volkan Cevher (NeurIPS, 2022)