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Brian Karrer
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2020 – today
- 2024
- [j4]Arjun Wilkins
, Daniel Kifer, Danfeng Zhang
Exact Privacy Analysis of the Gaussian Sparse Histogram Mechanism. J. Priv. Confidentiality 14(1) (2024) - [j3]Ashwini Pokle, Matthew J. Muckley, Ricky T. Q. Chen, Brian Karrer:
Training-free linear image inverses via flows. Trans. Mach. Learn. Res. 2024 (2024) - [c15]Guan-Horng Liu, Yaron Lipman, Maximilian Nickel, Brian Karrer, Evangelos A. Theodorou, Ricky T. Q. Chen:
Generalized Schrödinger Bridge Matching. ICLR 2024 - [c14]Heli Ben-Hamu, Omri Puny, Itai Gat, Brian Karrer, Uriel Singer, Yaron Lipman:
D-Flow: Differentiating through Flows for Controlled Generation. ICML 2024 - [i27]Heli Ben-Hamu, Omri Puny, Itai Gat, Brian Karrer, Uriel Singer, Yaron Lipman:
D-Flow: Differentiating through Flows for Controlled Generation. CoRR abs/2402.14017 (2024) - [i26]Carles Domingo-Enrich, Michal Drozdzal, Brian Karrer, Ricky T. Q. Chen:
Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control. CoRR abs/2409.08861 (2024) - [i25]Peter Holderrieth, Marton Havasi, Jason Yim, Neta Shaul, Itai Gat, Tommi S. Jaakkola, Brian Karrer, Ricky T. Q. Chen, Yaron Lipman:
Generator Matching: Generative modeling with arbitrary Markov processes. CoRR abs/2410.20587 (2024) - 2023
- [c13]Matthew Le, Apoorv Vyas, Bowen Shi, Brian Karrer, Leda Sari, Rashel Moritz, Mary Williamson, Vimal Manohar, Yossi Adi, Jay Mahadeokar, Wei-Ning Hsu:
Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale. NeurIPS 2023 - [c12]Yuhao Li
HHVM Performance Optimization for Large Scale Web Services. ICPE 2023: 137-148 - [i24]Alexandre Sablayrolles, Yue Wang, Brian Karrer:
Privately generating tabular data using language models. CoRR abs/2306.04803 (2023) - [i23]Matthew Le, Apoorv Vyas, Bowen Shi, Brian Karrer, Leda Sari, Rashel Moritz, Mary Williamson, Vimal Manohar, Yossi Adi, Jay Mahadeokar, Wei-Ning Hsu:
Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale. CoRR abs/2306.15687 (2023) - [i22]Lili Yu, Bowen Shi, Ramakanth Pasunuru, Benjamin Muller, Olga Golovneva, Tianlu Wang, Arun Babu, Binh Tang, Brian Karrer, Shelly Sheynin, Candace Ross, Adam Polyak, Russell Howes, Vasu Sharma, Puxin Xu, Hovhannes Tamoyan, Oron Ashual, Uriel Singer, Shang-Wen Li, Susan Zhang, Richard James, Gargi Ghosh, Yaniv Taigman, Maryam Fazel-Zarandi, Asli Celikyilmaz, Luke Zettlemoyer, Armen Aghajanyan:
Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning. CoRR abs/2309.02591 (2023) - [i21]Guan-Horng Liu, Yaron Lipman, Maximilian Nickel
Generalized Schrödinger Bridge Matching. CoRR abs/2310.02233 (2023) - [i20]Ashwini Pokle, Matthew J. Muckley, Ricky T. Q. Chen, Brian Karrer:
Training-free Linear Image Inversion via Flows. CoRR abs/2310.04432 (2023) - 2022
- [c11]Chuan Guo, Brian Karrer, Kamalika Chaudhuri, Laurens van der Maaten:
Bounding Training Data Reconstruction in Private (Deep) Learning. ICML 2022: 8056-8071 - [i19]Chuan Guo, Brian Karrer, Kamalika Chaudhuri, Laurens van der Maaten:
Bounding Training Data Reconstruction in Private (Deep) Learning. CoRR abs/2201.12383 (2022) - [i18]Brian Karrer, Daniel Kifer, Arjun Wilkins, Danfeng Zhang:
Exact Privacy Analysis of the Gaussian Sparse Histogram Mechanism. CoRR abs/2202.01100 (2022) - 2021
- [j2]Carlos Alberto Gomez-Uribe, Brian Karrer:
The Decoupled Extended Kalman Filter for Dynamic Exponential-Family Factorization Models. J. Mach. Learn. Res. 22: 5:1-5:25 (2021) - [c10]Brian Karrer, Liang Shi, Monica Bhole, Matt Goldman, Tyrone Palmer, Charlie Gelman, Mikael Konutgan, Feng Sun:
Network Experimentation at Scale. KDD 2021: 3106-3116 - 2020
- [c9]Shali Jiang, Daniel R. Jiang, Maximilian Balandat, Brian Karrer, Jacob R. Gardner, Roman Garnett:
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees. NeurIPS 2020 - [c8]Maximilian Balandat, Brian Karrer, Daniel R. Jiang, Samuel Daulton, Benjamin Letham, Andrew Gordon Wilson, Eytan Bakshy:
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization. NeurIPS 2020 - [i17]Shali Jiang, Daniel R. Jiang, Maximilian Balandat, Brian Karrer, Jacob R. Gardner, Roman Garnett:
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees. CoRR abs/2006.15779 (2020) - [i16]Brian Karrer, Liang Shi, Monica Bhole, Matt Goldman, Tyrone Palmer, Charlie Gelman, Mikael Konutgan, Feng Sun:
Network experimentation at scale. CoRR abs/2012.08591 (2020)
2010 – 2019
- 2019
- [i15]Maximilian Balandat, Brian Karrer, Daniel R. Jiang, Samuel Daulton, Benjamin Letham, Andrew Gordon Wilson, Eytan Bakshy:
BoTorch: Programmable Bayesian Optimization in PyTorch. CoRR abs/1910.06403 (2019) - 2018
- [i14]Carlos Alberto Gomez-Uribe, Brian Karrer:
The decoupled extended Kalman filter for dynamic exponential-family factorization models. CoRR abs/1806.09976 (2018) - 2017
- [j1]Igor Kabiljo, Brian Karrer, Mayank Pundir, Sergey Pupyrev, Alon Shalita, Yaroslav Akhremtsev, Alessandro Presta:
Social Hash Partitioner: A Scalable Distributed Hypergraph Partitioner. Proc. VLDB Endow. 10(11): 1418-1429 (2017) - [i13]Tim Danford, Onur Filiz, Jing Huang, Brian Karrer, Manohar Paluri, Guan Pang, Vish Ponnampalam, Nicolás Stier Moses, Birce Tezel:
End-to-end Planning of Fixed Millimeter-Wave Networks. CoRR abs/1705.07249 (2017) - [i12]Benjamin Letham, Brian Karrer, Guilherme Ottoni, Eytan Bakshy:
Constrained Bayesian Optimization with Noisy Experiments. CoRR abs/1706.07094 (2017) - [i11]Igor Kabiljo, Brian Karrer, Mayank Pundir, Sergey Pupyrev, Alon Shalita, Alessandro Presta, Yaroslav Akhremtsev:
Social Hash Partitioner: A Scalable Distributed Hypergraph Partitioner. CoRR abs/1707.06665 (2017) - 2016
- [c7]Laxman Dhulipala, Igor Kabiljo, Brian Karrer, Giuseppe Ottaviano, Sergey Pupyrev, Alon Shalita:
Compressing Graphs and Indexes with Recursive Graph Bisection. KDD 2016: 1535-1544 - [c6]Alon Shalita, Brian Karrer, Igor Kabiljo, Arun Sharma, Alessandro Presta, Aaron Adcock, Herald Kllapi, Michael Stumm:
Social Hash: An Assignment Framework for Optimizing Distributed Systems Operations on Social Networks. NSDI 2016: 455-468 - [i10]Laxman Dhulipala, Igor Kabiljo, Brian Karrer, Giuseppe Ottaviano, Sergey Pupyrev, Alon Shalita:
Compressing Graphs and Indexes with Recursive Graph Bisection. CoRR abs/1602.08820 (2016) - 2014
- [i9]Dean Eckles, Brian Karrer, Johan Ugander:
Design and analysis of experiments in networks: Reducing bias from interference. CoRR abs/1404.7530 (2014) - [i8]Brian Karrer, Mark E. J. Newman, Lenka Zdeborová:
Percolation on sparse networks. CoRR abs/1405.0483 (2014) - 2013
- [c5]Michael S. Bernstein, Eytan Bakshy, Moira Burke, Brian Karrer:
Quantifying the invisible audience in social networks. CHI 2013: 21-30 - [c4]Johan Ugander, Brian Karrer, Lars Backstrom, Jon M. Kleinberg:
Graph cluster randomization: network exposure to multiple universes. KDD 2013: 329-337 - [i7]Travis Martin, Brian Ball, Brian Karrer, M. E. J. Newman:
Coauthorship and citation in scientific publishing. CoRR abs/1304.0473 (2013) - [i6]Johan Ugander, Brian Karrer, Lars Backstrom, Jon M. Kleinberg:
Graph cluster randomization: network exposure to multiple universes. CoRR abs/1305.6979 (2013) - 2011
- [c3]Brendan Meeder, Brian Karrer, Amin Sayedi, R. Ravi, Christian Borgs
We know who you followed last summer: inferring social link creation times in twitter. WWW 2011: 517-526 - [i5]Brian Ball, Brian Karrer, M. E. J. Newman:
An efficient and principled method for detecting communities in networks. CoRR abs/1104.3590 (2011) - [i4]Brian Karrer, M. E. J. Newman:
Competing epidemics on complex networks. CoRR abs/1105.3424 (2011) - [i3]Johan Ugander, Brian Karrer, Lars Backstrom, Cameron Marlow:
The Anatomy of the Facebook Social Graph. CoRR abs/1111.4503 (2011) - 2010
- [c2]Christian Borgs
Game-Theoretic Models of Information Overload in Social Networks. WAW 2010: 146-161 - [i2]Brian Karrer, M. E. J. Newman:
Random graphs containing arbitrary distributions of subgraphs. CoRR abs/1005.1659 (2010) - [i1]Brian Karrer, M. E. J. Newman:
Stochastic blockmodels and community structure in networks. CoRR abs/1008.3926 (2010)
2000 – 2009
- 2009
- [c1]Eytan Bakshy, Brian Karrer, Lada A. Adamic:
Social influence and the diffusion of user-created content. EC 2009: 325-334
Coauthor Index
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