Isik, Berivan

22 publications

ICML 2025 Leveraging Per-Instance Privacy for Machine Unlearning Nazanin Mohammadi Sepahvand, Anvith Thudi, Berivan Isik, Ashmita Bhattacharyya, Nicolas Papernot, Eleni Triantafillou, Daniel M. Roy, Gintare Karolina Dziugaite

ICLR 2025 Scaling Laws for Downstream Task Performance in Machine Translation Berivan Isik, Natalia Ponomareva, Hussein Hazimeh, Dimitris Paparas, Sergei Vassilvitskii, Sanmi Koyejo

AISTATS 2024 Adaptive Compression in Federated Learning via Side Information Berivan Isik, Francesco Pase, Deniz Gunduz, Sanmi Koyejo, Tsachy Weissman, Michele Zorzi

ICML 2024 Improved Communication-Privacy Trade-Offs in $l_2$ Mean Estimation Under Streaming Differential Privacy Wei-Ning Chen, Berivan Isik, Peter Kairouz, Albert No, Sewoong Oh, Zheng Xu

ICMLW 2024 Lottery Ticket Adaptation: Mitigating Destructive Interference in LLMs Ashwinee Panda, Berivan Isik, Xiangyu Qi, Sanmi Koyejo, Tsachy Weissman, Prateek Mittal

ICMLW 2024 Lottery Ticket Adaptation: Mitigating Destructive Interference in LLMs Ashwinee Panda, Berivan Isik, Xiangyu Qi, Sanmi Koyejo, Tsachy Weissman, Prateek Mittal

ICMLW 2024 Lottery Ticket Adaptation: Mitigating Destructive Interference in LLMs Ashwinee Panda, Berivan Isik, Xiangyu Qi, Sanmi Koyejo, Tsachy Weissman, Prateek Mittal

ICLRW 2024 On Fairness Implications and Evaluations of Low-Rank Adaptation of Large Models Ken Liu, Zhoujie Ding, Berivan Isik, Sanmi Koyejo

ICLRW 2024 Scaling Laws for Downstream Task Performance of Large Language Models Berivan Isik, Natalia Ponomareva, Hussein Hazimeh, Dimitris Paparas, Sergei Vassilvitskii, Sanmi Koyejo

NeurIPS 2024 Sketching for Distributed Deep Learning: A Sharper Analysis Mayank Shrivastava, Berivan Isik, Qiaobo Li, Sanmi Koyejo, Arindam Banerjee

ICLRW 2024 Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations Rylan Schaeffer, Berivan Isik, Dhruv Bhandarkar Pai, Andres Carranza, Victor Lecomte, Alyssa Unell, Mikail Khona, Thomas Edward Yerxa, Yann LeCun, SueYeon Chung, Andrey Gromov, Ravid Shwartz-Ziv, Sanmi Koyejo

NeurIPSW 2023 An Information-Theoretic Understanding of Maximum Manifold Capacity Representations Rylan Schaeffer, Berivan Isik, Victor Lecomte, Mikail Khona, Yann LeCun, Andrey Gromov, Ravid Shwartz-Ziv, Sanmi Koyejo

NeurIPSW 2023 An Information-Theoretic Understanding of Maximum Manifold Capacity Representations Victor Lecomte, Rylan Schaeffer, Berivan Isik, Mikail Khona, Yann LeCun, Sanmi Koyejo, Andrey Gromov, Ravid Shwartz-Ziv

NeurIPSW 2023 An Information-Theoretic Understanding of Maximum Manifold Capacity Representations Berivan Isik, Victor Lecomte, Rylan Schaeffer, Yann LeCun, Mikail Khona, Ravid Shwartz-Ziv, Sanmi Koyejo, Andrey Gromov

ICMLW 2023 Exact Optimality in Communication-Privacy-Utility Tradeoffs Berivan Isik, Wei-Ning Chen, Ayfer Ozgur, Tsachy Weissman, Albert No

NeurIPS 2023 Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean Estimation Berivan Isik, Wei-Ning Chen, Ayfer Ozgur, Tsachy Weissman, Albert No

ICMLW 2023 GPT-Zip: Deep Compression of Finetuned Large Language Models Berivan Isik, Hermann Kumbong, Wanyi Ning, Xiaozhe Yao, Sanmi Koyejo, Ce Zhang

ICMLW 2023 Leveraging Side Information for Communication-Efficient Federated Learning Berivan Isik, Francesco Pase, Deniz Gunduz, Sanmi Koyejo, Tsachy Weissman, Michele Zorzi

ICLR 2023 Sparse Random Networks for Communication-Efficient Federated Learning Berivan Isik, Francesco Pase, Deniz Gunduz, Tsachy Weissman, Zorzi Michele

AISTATS 2022 An Information-Theoretic Justification for Model Pruning Berivan Isik, Tsachy Weissman, Albert No

NeurIPSW 2022 Efficient Federated Random Subnetwork Training Francesco Pase, Berivan Isik, Deniz Gunduz, Tsachy Weissman, Michele Zorzi

NeurIPSW 2020 Noisy Neural Network Compression for Analog Storage Devices Berivan Isik, Kristy Choi, Xin Zheng, H.-S. Philip Wong, Stefano Ermon, Tsachy Weissman, Armin Alaghi