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ORCIDDaniel LeJeune
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2020 – today
- 2024
[j4]Daniel LeJeune, Jiayu Liu, Reinhard Heckel:
Monotonic Risk Relationships under Distribution Shifts for Regularized Risk Minimization. J. Mach. Learn. Res. 25: 54:1-54:37 (2024)- [j3]Daniel LeJeune, Pratik Patil, Hamid Javadi, Richard G. Baraniuk, Ryan J. Tibshirani:
Asymptotics of the Sketched Pseudoinverse. SIAM J. Math. Data Sci. 6(1): 199-225 (2024) - [j2]Yehuda Dar, Daniel LeJeune, Richard G. Baraniuk:
The Common Intuition to Transfer Learning Can Win or Lose: Case Studies for Linear Regression. SIAM J. Math. Data Sci. 6(2): 454-480 (2024) - [c13]Lorenzo Luzi, Daniel LeJeune, Ali Siahkoohi, Sina Alemohammad, Vishwanath Saragadam, Hossein Babaei, Naiming Liu, Zichao Wang, Richard G. Baraniuk:
Titan: Bringing the Deep Image Prior to Implicit Representations. ICASSP 2024: 6165-6169 - [c12]Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi, Ahmed Imtiaz Humayun, Hossein Babaei, Daniel LeJeune, Ali Siahkoohi, Richard G. Baraniuk:
Self-Consuming Generative Models Go MAD. ICLR 2024 - [c11]Pratik Patil, Daniel LeJeune:
Asymptotically Free Sketched Ridge Ensembles: Risks, Cross-Validation, and Tuning. ICLR 2024 - [i13]Michal Derezinski
, Daniel LeJeune, Deanna Needell, Elizaveta Rebrova:
Fine-grained Analysis and Faster Algorithms for Iteratively Solving Linear Systems. CoRR abs/2405.05818 (2024) - 2023
- [c10]Jasper Tan, Daniel LeJeune, Blake Mason, Hamid Javadi, Richard G. Baraniuk:
A Blessing of Dimensionality in Membership Inference through Regularization. AISTATS 2023: 10968-10993 - [c9]Vishwanath Saragadam, Daniel LeJeune, Jasper Tan, Guha Balakrishnan, Ashok Veeraraghavan, Richard G. Baraniuk:
WIRE: Wavelet Implicit Neural Representations. CVPR 2023: 18507-18516 - [i12]Vishwanath Saragadam, Daniel LeJeune, Jasper Tan, Guha Balakrishnan, Ashok Veeraraghavan, Richard G. Baraniuk:
WIRE: Wavelet Implicit Neural Representations. CoRR abs/2301.05187 (2023) - [i11]Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi, Ahmed Imtiaz Humayun, Hossein Babaei, Daniel LeJeune, Ali Siahkoohi, Richard G. Baraniuk:
Self-Consuming Generative Models Go MAD. CoRR abs/2307.01850 (2023) - [i10]Daniel LeJeune, Sina Alemohammad:
An Adaptive Tangent Feature Perspective of Neural Networks. CoRR abs/2308.15478 (2023) - 2022
- [j1]Pavan K. Kota, Daniel LeJeune, Rebekah A. Drezek, Richard G. Baraniuk:
Extreme Compressed Sensing of Poisson Rates From Multiple Measurements. IEEE Trans. Signal Process. 70: 2388-2401 (2022) - [i9]Jasper Tan, Daniel LeJeune, Blake Mason, Hamid Javadi, Richard G. Baraniuk:
Benign Overparameterization in Membership Inference with Early Stopping. CoRR abs/2205.14055 (2022) - [i8]Daniel LeJeune, Jiayu Liu, Reinhard Heckel:
Monotonic Risk Relationships under Distribution Shifts for Regularized Risk Minimization. CoRR abs/2210.11589 (2022) - [i7]Daniel LeJeune, Pratik Patil, Hamid Javadi, Richard G. Baraniuk, Ryan J. Tibshirani:
Asymptotics of the Sketched Pseudoinverse. CoRR abs/2211.03751 (2022) - 2021
- [c8]Tianyi Yao, Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk, Genevera I. Allen:
Minipatch Learning as Implicit Ridge-Like Regularization. BigComp 2021: 65-68 - [c7]Sina Alemohammad, Hossein Babaei, Randall Balestriero, Matt Y. Cheung, Ahmed Imtiaz Humayun, Daniel LeJeune, Naiming Liu, Lorenzo Luzi, Jasper Tan, Zichao Wang, Richard G. Baraniuk:
Wearing A Mask: Compressed Representations of Variable-Length Sequences Using Recurrent Neural Tangent Kernels. ICASSP 2021: 2950-2954 - [c6]Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk:
The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization. NeurIPS 2021: 23401-23412 - [i6]Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk:
The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization. CoRR abs/2106.07769 (2021) - 2020
- [c5]Daniel LeJeune, Gautam Dasarathy, Richard G. Baraniuk:
Thresholding Graph Bandits with GrAPL. AISTATS 2020: 2476-2485 - [c4]Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk:
The Implicit Regularization of Ordinary Least Squares Ensembles. AISTATS 2020: 3525-3535 - [i5]Sina Alemohammad, Hossein Babaei, Randall Balestriero, Matt Y. Cheung, Ahmed Imtiaz Humayun, Daniel LeJeune, Naiming Liu, Lorenzo Luzi, Jasper Tan, Zichao Wang, Richard G. Baraniuk:
Wearing a MASK: Compressed Representations of Variable-Length Sequences Using Recurrent Neural Tangent Kernels. CoRR abs/2010.13975 (2020)
2010 – 2019
- 2019
- [c3]Daniel LeJeune, Reinhard Heckel, Richard G. Baraniuk:
Adaptive Estimation for Approximate k-Nearest-Neighbor Computations. AISTATS 2019: 3099-3107 - [i4]Daniel LeJeune, Richard G. Baraniuk, Reinhard Heckel:
Adaptive Estimation for Approximate k-Nearest-Neighbor Computations. CoRR abs/1902.09465 (2019) - [i3]Daniel LeJeune, Gautam Dasarathy, Richard G. Baraniuk:
Thresholding Graph Bandits with GrAPL. CoRR abs/1905.09190 (2019) - [i2]Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk:
The Implicit Regularization of Ordinary Least Squares Ensembles. CoRR abs/1910.04743 (2019) - 2018
- [c2]Jason Matterer, Daniel LeJeune:
Peer Group Metadata-Informed LSTM Ensembles for Insider Threat Detection. FLAIRS 2018: 62-67 - [c1]Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava, Richard G. Baraniuk:
MISSION: Ultra Large-Scale Feature Selection using Count-Sketches. ICML 2018: 80-88 - [i1]Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava, Richard G. Baraniuk:
MISSION: Ultra Large-Scale Feature Selection using Count-Sketches. CoRR abs/1806.04310 (2018)
Coauthor Index
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last updated on 2024-10-07 22:10 CEST by the dblp team
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