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2020 – today
- 2022
[j25]De Huang, Jonathan Niles-Weed, Joel A. Tropp, Rachel Ward:
Matrix Concentration for Products. Found. Comput. Math. 22(6): 1767-1799 (2022)- [c17]Xiaoxia Wu, Yuege Xie, Simon Shaolei Du, Rachel Ward:
AdaLoss: A Computationally-Efficient and Provably Convergent Adaptive Gradient Method. AAAI 2022: 8691-8699 - [c16]Matthew Faw, Isidoros Tziotis, Constantine Caramanis, Aryan Mokhtari, Sanjay Shakkottai, Rachel Ward:
The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance. COLT 2022: 313-355 - [c15]Itay Evron, Edward Moroshko, Rachel Ward, Nathan Srebro, Daniel Soudry:
How catastrophic can catastrophic forgetting be in linear regression? COLT 2022: 4028-4079 - [c14]Abhinav Nellore, Rachel Ward:
Arbitrary-Length Analogs to de Bruijn Sequences. CPM 2022: 9:1-9:20 - [i46]Matthew Faw, Isidoros Tziotis, Constantine Caramanis, Aryan Mokhtari, Sanjay Shakkottai, Rachel Ward:
The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance. CoRR abs/2202.05791 (2022) - [i45]Shuo Yang, Yijun Dong, Rachel Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei:
Sample Efficiency of Data Augmentation Consistency Regularization. CoRR abs/2202.12230 (2022) - [i44]Juncai He, Richard Tsai, Rachel Ward:
Side-effects of Learning from Low Dimensional Data Embedded in an Euclidean Space. CoRR abs/2203.00614 (2022) - [i43]Zhijun Chen, Hayden Schaeffer, Rachel Ward:
Concentration of Random Feature Matrices in High-Dimensions. CoRR abs/2204.06935 (2022) - [i42]Ruhui Jin, Joe Kileel, Tamara G. Kolda, Rachel Ward:
Scalable symmetric Tucker tensor decomposition. CoRR abs/2204.10824 (2022) - [i41]Nhat Ho, Tongzheng Ren, Sujay Sanghavi, Purnamrita Sarkar, Rachel Ward:
An Exponentially Increasing Step-size for Parameter Estimation in Statistical Models. CoRR abs/2205.07999 (2022) - [i40]Itay Evron, Edward Moroshko, Rachel Ward, Nati Srebro, Daniel Soudry:
How catastrophic can catastrophic forgetting be in linear regression? CoRR abs/2205.09588 (2022) - [i39]Raghu Bollapragada, Tyler Chen, Rachel Ward:
On the fast convergence of minibatch heavy ball momentum. CoRR abs/2206.07553 (2022) - [i38]Yijun Dong, Yuege Xie, Rachel Ward:
AdaWAC: Adaptively Weighted Augmentation Consistency Regularization for Volumetric Medical Image Segmentation. CoRR abs/2210.01891 (2022) - 2021
- [c13]De Huang, Jonathan Niles-Weed, Rachel Ward:
Streaming k-PCA: Efficient guarantees for Oja's algorithm, beyond rank-one updates. COLT 2021: 2463-2498 - [c12]Robert Lunde, Purnamrita Sarkar, Rachel Ward:
Bootstrapping the Error of Oja's Algorithm. NeurIPS 2021: 6240-6252 - [i37]De Huang, Jonathan Niles-Weed, Rachel Ward:
Streaming k-PCA: Efficient guarantees for Oja's algorithm, beyond rank-one updates. CoRR abs/2102.03646 (2021) - [i36]Abolfazl Hashemi, Hayden Schaeffer, Robert Shi, Ufuk Topcu, Giang Tran, Rachel Ward:
Function Approximation via Sparse Random Features. CoRR abs/2103.03191 (2021) - [i35]Stefan Bamberger, Felix Krahmer, Rachel Ward:
Johnson-Lindenstrauss Embeddings with Kronecker Structure. CoRR abs/2106.13349 (2021) - [i34]Abhinav Nellore, Rachel Ward:
Arbitrary-length analogs to de Bruijn sequences. CoRR abs/2108.07759 (2021) - [i33]Xiaoxia Wu, Yuege Xie, Simon S. Du, Rachel Ward:
AdaLoss: A computationally-efficient and provably convergent adaptive gradient method. CoRR abs/2109.08282 (2021) - [i32]Dimitris Giannakis, Amelia Henriksen, Joel A. Tropp, Rachel Ward:
Learning to Forecast Dynamical Systems from Streaming Data. CoRR abs/2109.09703 (2021) - [i31]Yuege Xie, Bobby Shi, Hayden Schaeffer, Rachel Ward:
SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning. CoRR abs/2112.04002 (2021) - 2020
- [j24]Lam Si Tung Ho, Hayden Schaeffer
, Giang Tran, Rachel Ward:
Recovery guarantees for polynomial coefficients from weakly dependent data with outliers. J. Approx. Theory 259: 105472 (2020) - [j23]Hayden Schaeffer, Giang Tran, Rachel Ward, Linan Zhang:
Extracting Structured Dynamical Systems Using Sparse Optimization With Very Few Samples. Multiscale Model. Simul. 18(4): 1435-1461 (2020) - [c11]Yuege Xie, Xiaoxia Wu, Rachel Ward:
Linear Convergence of Adaptive Stochastic Gradient Descent. AISTATS 2020: 1475-1485 - [c10]Xiaoxia Wu, Edgar Dobriban, Tongzheng Ren, Shanshan Wu, Zhiyuan Li, Suriya Gunasekar, Rachel Ward, Qiang Liu:
Implicit Regularization and Convergence for Weight Normalization. NeurIPS 2020 - [e1]Jianfeng Lu, Rachel Ward:
Proceedings of Mathematical and Scientific Machine Learning, MSML 2020, 20-24 July 2020, Virtual Conference / Princeton, NJ, USA. Proceedings of Machine Learning Research 107, PMLR 2020 [contents] - [i30]Yuege Xie, Rachel Ward, Holger Rauhut, Hung-Hsu Chou:
Weighted Optimization: better generalization by smoother interpolation. CoRR abs/2006.08495 (2020)
2010 – 2019
- 2019
- [c9]Rachel Ward, Xiaoxia Wu, Léon Bottou:
AdaGrad stepsizes: sharp convergence over nonconvex landscapes. ICML 2019: 6677-6686 - [i29]Xiaoxia Wu, Simon S. Du, Rachel Ward:
Global Convergence of Adaptive Gradient Methods for An Over-parameterized Neural Network. CoRR abs/1902.07111 (2019) - [i28]Amelia Henriksen, Rachel Ward:
AdaOja: Adaptive Learning Rates for Streaming PCA. CoRR abs/1905.12115 (2019) - [i27]Denali Molitor, Deanna Needell, Rachel Ward:
Bias of Homotopic Gradient Descent for the Hinge Loss. CoRR abs/1907.11746 (2019) - [i26]Yuege Xie, Xiaoxia Wu, Rachel Ward:
Linear Convergence of Adaptive Stochastic Gradient Descent. CoRR abs/1908.10525 (2019) - [i25]Ruhui Jin, Tamara G. Kolda, Rachel Ward:
Faster Johnson-Lindenstrauss Transforms via Kronecker Products. CoRR abs/1909.04801 (2019) - [i24]Xiaoxia Wu, Edgar Dobriban, Tongzheng Ren, Shanshan Wu, Zhiyuan Li, Suriya Gunasekar, Rachel Ward, Qiang Liu:
Implicit Regularization of Normalization Methods. CoRR abs/1911.07956 (2019) - 2018
- [j22]Hayden Schaeffer, Giang Tran, Rachel Ward:
Extracting Sparse High-Dimensional Dynamics from Limited Data. SIAM J. Appl. Math. 78(6): 3279-3295 (2018) - [i23]Xiaoxia Wu, Rachel Ward, Léon Bottou:
WNGrad: Learn the Learning Rate in Gradient Descent. CoRR abs/1803.02865 (2018) - [i22]Christopher Kennedy, Rachel Ward:
Greedy Variance Estimation for the LASSO. CoRR abs/1803.10878 (2018) - [i21]Hayden Schaeffer, Giang Tran, Rachel Ward, Linan Zhang:
Extracting structured dynamical systems using sparse optimization with very few samples. CoRR abs/1805.04158 (2018) - [i20]Rachel Ward, Xiaoxia Wu, Léon Bottou:
AdaGrad stepsizes: Sharp convergence over nonconvex landscapes, from any initialization. CoRR abs/1806.01811 (2018) - [i19]Lam Si Tung Ho, Hayden Schaeffer, Giang Tran, Rachel Ward:
Recovery guarantees for polynomial approximation from dependent data with outliers. CoRR abs/1811.10115 (2018) - 2017
- [j21]Giang Tran, Rachel Ward:
Exact Recovery of Chaotic Systems from Highly Corrupted Data. Multiscale Model. Simul. 15(3): 1108-1129 (2017) - [c8]Christopher Kennedy, Rachel Ward:
Fast Cross-Polytope Locality-Sensitive Hashing. ITCS 2017: 53:1-53:16 - 2016
- [j20]Deanna Needell, Nathan Srebro, Rachel Ward:
Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm. Math. Program. 155(1-2): 549-573 (2016) - [j19]Karin Knudson, Rayan Saab, Rachel Ward:
One-Bit Compressive Sensing With Norm Estimation. IEEE Trans. Inf. Theory 62(5): 2748-2758 (2016) - [j18]Bubacarr Bah, Rachel Ward:
The Sample Complexity of Weighted Sparse Approximation. IEEE Trans. Signal Process. 64(12): 3145-3155 (2016) - [c7]Dustin G. Mixon, Soledad Villar, Rachel Ward:
Clustering subgaussian mixtures with k-means. ITW 2016: 211-215 - [i18]Dustin G. Mixon, Soledad Villar, Rachel Ward:
Clustering subgaussian mixtures by semidefinite programming. CoRR abs/1602.06612 (2016) - [i17]Christopher Kennedy, Rachel Ward:
Fast Cross-Polytope Locality-Sensitive Hashing. CoRR abs/1602.06922 (2016) - [i16]Deanna Needell, Rachel Ward:
Batched Stochastic Gradient Descent with Weighted Sampling. CoRR abs/1608.07641 (2016) - [i15]Shahar Mendelson, Holger Rauhut, Rachel Ward:
Improved bounds for sparse recovery from subsampled random convolutions. CoRR abs/1610.04983 (2016) - [i14]Soledad Villar, Afonso S. Bandeira, Andrew J. Blumberg, Rachel Ward:
A polynomial-time relaxation of the Gromov-Hausdorff distance. CoRR abs/1610.05214 (2016) - 2015
- [j17]Abhinav Nellore, Rachel Ward:
Recovery guarantees for exemplar-based clustering. Inf. Comput. 245: 165-180 (2015) - [j16]Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel Ward:
Completing any low-rank matrix, provably. J. Mach. Learn. Res. 16: 2999-3034 (2015) - [j15]Felix Krahmer, Deanna Needell, Rachel Ward:
Compressive Sensing with Redundant Dictionaries and Structured Measurements. SIAM J. Math. Anal. 47(6): 4606-4629 (2015) - [c6]Pranjal Awasthi, Afonso S. Bandeira, Moses Charikar, Ravishankar Krishnaswamy, Soledad Villar, Rachel Ward:
Relax, No Need to Round: Integrality of Clustering Formulations. ITCS 2015: 191-200 - [i13]Felix Krahmer, Deanna Needell, Rachel Ward:
Compressive Sensing with Redundant Dictionaries and Structured Measurements. CoRR abs/1501.03208 (2015) - [i12]Bubacarr Bah, Rachel Ward:
The sample complexity of weighted sparse approximation. CoRR abs/1507.06736 (2015) - 2014
- [j14]Felix Krahmer, Rachel Ward:
Stable and Robust Sampling Strategies for Compressive Imaging. IEEE Trans. Image Process. 23(2): 612-622 (2014) - [c5]Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel Ward:
Coherent Matrix Completion. ICML 2014: 674-682 - [c4]Deanna Needell, Rachel Ward, Nathan Srebro:
Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm. NIPS 2014: 1017-1025 - [i11]Rachel Ward:
A unified framework for linear dimensionality reduction in l1. CoRR abs/1405.1332 (2014) - [i10]Pranjal Awasthi, Afonso S. Bandeira, Moses Charikar, Ravishankar Krishnaswamy, Soledad Villar, Rachel Ward:
Relax, no need to round: integrality of clustering formulations. CoRR abs/1408.4045 (2014) - 2013
- [j13]Mark A. Iwen, Fadil Santosa, Rachel Ward:
A Symbol-Based Algorithm for Decoding Bar Codes. SIAM J. Imaging Sci. 6(1): 56-77 (2013) - [j12]Deanna Needell, Rachel Ward:
Stable Image Reconstruction Using Total Variation Minimization. SIAM J. Imaging Sci. 6(2): 1035-1058 (2013) - [j11]Deanna Needell, Rachel Ward:
Near-Optimal Compressed Sensing Guarantees for Total Variation Minimization. IEEE Trans. Image Process. 22(10): 3941-3949 (2013) - [i9]Srinadh Bhojanapalli, Yudong Chen, Sujay Sanghavi, Rachel Ward:
Coherent Matrix Completion. CoRR abs/1306.2979 (2013) - [i8]Abhinav Nellore, Rachel Ward:
Recovery guarantees for exemplar-based clustering. CoRR abs/1309.3256 (2013) - [i7]Deanna Needell, Nathan Srebro, Rachel Ward:
Stochastic gradient descent and the randomized Kaczmarz algorithm. CoRR abs/1310.5715 (2013) - 2012
- [j10]Holger Rauhut, Rachel Ward:
Sparse Legendre expansions via l1-minimization. J. Approx. Theory 164(5): 517-533 (2012) - [j9]Nicolas Burq, Semyon Dyatlov, Rachel Ward, Maciej Zworski:
Weighted Eigenfunction Estimates with Applications to Compressed Sensing. SIAM J. Math. Anal. 44(5): 3481-3501 (2012) - [j8]Felix Krahmer, Rayan Saab, Rachel Ward:
Root-Exponential Accuracy for Coarse Quantization of Finite Frame Expansions. IEEE Trans. Inf. Theory 58(2): 1069-1079 (2012) - [i6]Deanna Needell, Rachel Ward:
Stable image reconstruction using total variation minimization. CoRR abs/1202.6429 (2012) - [i5]Felix Krahmer, Rachel Ward:
Compressive imaging: stable and robust recovery from variable density frequency samples. CoRR abs/1210.2380 (2012) - [i4]Deanna Needell, Rachel Ward:
Total variation minimization for stable multidimensional signal recovery. CoRR abs/1210.3098 (2012) - [i3]Mark A. Iwen, Fadil Santosa, Rachel Ward:
A symbol-based algorithm for decoding bar codes. CoRR abs/1210.7009 (2012) - 2011
- [j7]William Perkins, Mark Tygert, Rachel Ward:
Computing the confidence levels for a root-mean-square test of goodness-of-fit. Appl. Math. Comput. 217(22): 9072-9084 (2011) - [j6]Massimo Fornasier, Holger Rauhut, Rachel Ward:
Low-rank Matrix Recovery via Iteratively Reweighted Least Squares Minimization. SIAM J. Optim. 21(4): 1614-1640 (2011) - [j5]Felix Krahmer, Rachel Ward:
New and Improved Johnson-Lindenstrauss Embeddings via the Restricted Isometry Property. SIAM J. Math. Anal. 43(3): 1269-1281 (2011) - [c3]Leanne M. Hirshfield, Rebecca Gulotta, Stuart H. Hirshfield, Samuel W. Hincks, Matthew Russell, Rachel Ward, Tom Williams, Robert J. K. Jacob:
This is your brain on interfaces: enhancing usability testing with functional near-infrared spectroscopy. CHI 2011: 373-382 - [c2]Leanne M. Hirshfield, Stuart H. Hirshfield, Samuel W. Hincks, Matthew Russell, Rachel Ward, Tom Williams:
Trust in Human-Computer Interactions as Measured by Frustration, Surprise, and Workload. HCI (20) 2011: 507-516 - 2010
- [j4]Massimo Fornasier, Rachel Ward:
Iterative Thresholding Meets Free-Discontinuity Problems. Found. Comput. Math. 10(5): 527-567 (2010) - [j3]Boris Alexeev, Rachel Ward:
On the Complexity of Mumford-Shah-Type Regularization, Viewed as a Relaxed Sparsity Constraint. IEEE Trans. Image Process. 19(10): 2787-2789 (2010) - [c1]Holger Rauhut, Rachel Ward:
Efficient and stable recovery of Legendre-sparse polynomials. CISS 2010: 1-6 - [i2]Felix Krahmer, Rachel Ward:
Lower bounds for the error decay incurred by coarse quantization schemes. CoRR abs/1004.3517 (2010) - [i1]Felix Krahmer, Rachel Ward:
New and improved Johnson-Lindenstrauss embeddings via the Restricted Isometry Property. CoRR abs/1009.0744 (2010)
2000 – 2009
- 2009
- [j2]Jeff Danciger, Satyan L. Devadoss, John Mugno, Don Sheehy, Rachel Ward:
Shape deformation in continuous map generalization. GeoInformatica 13(2): 203-221 (2009) - [j1]Rachel Ward:
Compressed sensing with cross validation. IEEE Trans. Inf. Theory 55(12): 5773-5782 (2009)
Coauthor Index
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last updated on 2022-12-12 01:10 CET by the dblp team
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