Rachel A. Ward

108 papers A* 12A 4B 2Misc 2Journal 83Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	First Proof. CoRR Mohammed Abouzaid, Andrew J. Blumberg, Martin Hairer, Joe Kileel, Tamara G. Kolda, Paul D. Nelson, Daniel Spielman, Nikhil Srivastava, Rachel A. Ward, Shmuel Weinberger, Lauren Williams
2024	J	`jnl`	Generating synthetic data for neural operators. CoRR Erisa Hasani, Rachel A. Ward
2024	J	`jnl`	Scalable Symmetric Tucker Tensor Decomposition. SIAM J. Matrix Anal. Appl. Ruhui Jin, Joe Kileel, Tamara G. Kolda, Rachel A. Ward
2023	A*	`conf`	Adaptively Weighted Data Augmentation Consistency Regularization for Robust Optimization under Concept Shift. ICML Yijun Dong, Yuege Xie, Rachel A. Ward
2023	J	`jnl`	Cluster-aware Semi-supervised Learning: Relational Knowledge Distillation Provably Learns Clustering. CoRR Yijun Dong, Kevin Miller, Qi Lei, Rachel A. Ward
2023	A*	`conf`	Convergence of Alternating Gradient Descent for Matrix Factorization. NeurIPS Rachel A. Ward, Tamara G. Kolda
2023	J	`jnl`	Convergence of Alternating Gradient Descent for Matrix Factorization. CoRR Rachel A. Ward, Tamara G. Kolda
2023	J	`jnl`	Learning to Forecast Dynamical Systems from Streaming Data. SIAM J. Appl. Dyn. Syst. Dimitrios Giannakis, Amelia Henriksen, Joel A. Tropp, Rachel A. Ward
2023	A*	`conf`	Nearly Optimal Bounds for Cyclic Forgetting. NeurIPS William Swartworth, Deanna Needell, Rachel A. Ward, Mark Kong, Halyun Jeong
2023	J	`jnl`	Robust Implicit Regularization via Weight Normalization. CoRR Hung-Hsu Chou, Holger Rauhut, Rachel A. Ward
2023	A	`conf`	Sample Efficiency of Data Augmentation Consistency Regularization. AISTATS Shuo Yang, Yijun Dong, Rachel A. Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei
2022	A*	`conf`	AdaLoss: A Computationally-Efficient and Provably Convergent Adaptive Gradient Method. AAAI Xiaoxia Wu, Yuege Xie, Simon Shaolei Du, Rachel A. Ward
2022	J	`jnl`	AdaWAC: Adaptively Weighted Augmentation Consistency Regularization for Volumetric Medical Image Segmentation. CoRR Yijun Dong, Yuege Xie, Rachel A. Ward
2022	J	`jnl`	An Exponentially Increasing Step-size for Parameter Estimation in Statistical Models. CoRR Nhat Ho, Tongzheng Ren, Sujay Sanghavi, Purnamrita Sarkar, Rachel A. Ward
2022	B	`conf`	Arbitrary-Length Analogs to de Bruijn Sequences. CPM Abhinav Nellore, Rachel A. Ward
2022	J	`jnl`	Compressed sensing with a jackknife and a bootstrap. J. Data Sci. Stat. Vis. Aaron Defazio, Mark Tygert, Rachel A. Ward, Jure Zbontar
2022	—	`conf`	Concentration of Random Feature Matrices in High-Dimensions. MSML Zhijun Chen, Hayden Schaeffer, Rachel A. Ward
2022	J	`jnl`	Concentration of Random Feature Matrices in High-Dimensions. CoRR Zhijun Chen, Hayden Schaeffer, Rachel A. Ward
2022	A*	`conf`	How catastrophic can catastrophic forgetting be in linear regression? COLT Itay Evron, Edward Moroshko, Rachel A. Ward, Nathan Srebro, Daniel Soudry
2022	J	`jnl`	How catastrophic can catastrophic forgetting be in linear regression? CoRR Itay Evron, Edward Moroshko, Rachel A. Ward, Nati Srebro, Daniel Soudry
2022	J	`jnl`	Johnson-Lindenstrauss Embeddings with Kronecker Structure. SIAM J. Matrix Anal. Appl. Stefan Bamberger, Felix Krahmer, Rachel A. Ward
2022	J	`jnl`	Matrix Concentration for Products. Found. Comput. Math. De Huang, Jonathan Niles-Weed, Joel A. Tropp, Rachel A. Ward
2022	J	`jnl`	On the fast convergence of minibatch heavy ball momentum. CoRR Raghu Bollapragada, Tyler Chen, Rachel A. Ward
2022	J	`jnl`	Overparameterization and Generalization Error: Weighted Trigonometric Interpolation. SIAM J. Math. Data Sci. Yuege Xie, Hung-Hsu Chou, Holger Rauhut, Rachel A. Ward
2022	—	`conf`	SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning. MSML Yuege Xie, Robert Shi, Hayden Schaeffer, Rachel A. Ward
2022	J	`jnl`	Sample Efficiency of Data Augmentation Consistency Regularization. CoRR Shuo Yang, Yijun Dong, Rachel A. Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei
2022	J	`jnl`	Scalable symmetric Tucker tensor decomposition. CoRR Ruhui Jin, Joe Kileel, Tamara G. Kolda, Rachel A. Ward
2022	J	`jnl`	Side-effects of Learning from Low Dimensional Data Embedded in an Euclidean Space. CoRR Juncai He, Richard Tsai, Rachel A. Ward
2022	A*	`conf`	The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance. COLT Matthew Faw, Isidoros Tziotis, Constantine Caramanis, Aryan Mokhtari, Sanjay Shakkottai, Rachel A. Ward
2022	J	`jnl`	The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance. CoRR Matthew Faw, Isidoros Tziotis, Constantine Caramanis, Aryan Mokhtari, Sanjay Shakkottai, Rachel A. Ward
2021	J	`jnl`	AdaLoss: A computationally-efficient and provably convergent adaptive gradient method. CoRR Xiaoxia Wu, Yuege Xie, Simon S. Du, Rachel A. Ward
2021	J	`jnl`	Arbitrary-length analogs to de Bruijn sequences. CoRR Abhinav Nellore, Rachel A. Ward
2021	A*	`conf`	Bootstrapping the Error of Oja's Algorithm. NeurIPS Robert Lunde, Purnamrita Sarkar, Rachel A. Ward
2021	J	`jnl`	Function Approximation via Sparse Random Features. CoRR Abolfazl Hashemi, Hayden Schaeffer, Robert Shi, Ufuk Topcu, Giang Tran, Rachel A. Ward
2021	J	`jnl`	Johnson-Lindenstrauss Embeddings with Kronecker Structure. CoRR Stefan Bamberger, Felix Krahmer, Rachel A. Ward
2021	J	`jnl`	Learning to Forecast Dynamical Systems from Streaming Data. CoRR Dimitris Giannakis, Amelia Henriksen, Joel A. Tropp, Rachel A. Ward
2021	J	`jnl`	SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning. CoRR Yuege Xie, Bobby Shi, Hayden Schaeffer, Rachel A. Ward
2021	A*	`conf`	Streaming k-PCA: Efficient guarantees for Oja's algorithm, beyond rank-one updates. COLT De Huang, Jonathan Niles-Weed, Rachel A. Ward
2021	J	`jnl`	Streaming k-PCA: Efficient guarantees for Oja's algorithm, beyond rank-one updates. CoRR De Huang, Jonathan Niles-Weed, Rachel A. Ward
2020	J	`jnl`	Extracting Structured Dynamical Systems Using Sparse Optimization With Very Few Samples. Multiscale Model. Simul. Hayden Schaeffer, Giang Tran, Rachel A. Ward, Linan Zhang
2020	A*	`conf`	Implicit Regularization and Convergence for Weight Normalization. NeurIPS Xiaoxia Wu, Edgar Dobriban, Tongzheng Ren, Shanshan Wu, Zhiyuan Li, Suriya Gunasekar, Rachel A. Ward, Qiang Liu
2020	A	`conf`	Linear Convergence of Adaptive Stochastic Gradient Descent. AISTATS Yuege Xie, Xiaoxia Wu, Rachel A. Ward
2020	—	`ed.`	Proceedings of Mathematical and Scientific Machine Learning, MSML 2020, 20-24 July 2020, Virtual Conference / Princeton, NJ, USA MSML Jianfeng Lu, Rachel A. Ward
2020	J	`jnl`	Recovery guarantees for polynomial coefficients from weakly dependent data with outliers. J. Approx. Theory Lam Si Tung Ho, Hayden Schaeffer, Giang Tran, Rachel A. Ward
2020	J	`jnl`	Weighted Optimization: better generalization by smoother interpolation. CoRR Yuege Xie, Rachel A. Ward, Holger Rauhut, Hung-Hsu Chou
2019	A*	`conf`	AdaGrad stepsizes: sharp convergence over nonconvex landscapes. ICML Rachel A. Ward, Xiaoxia Wu, Léon Bottou
2019	J	`jnl`	AdaOja: Adaptive Learning Rates for Streaming PCA. CoRR Amelia Henriksen, Rachel A. Ward
2019	J	`jnl`	Bias of Homotopic Gradient Descent for the Hinge Loss. CoRR Denali Molitor, Deanna Needell, Rachel A. Ward
2019	J	`jnl`	Faster Johnson-Lindenstrauss Transforms via Kronecker Products. CoRR Ruhui Jin, Tamara G. Kolda, Rachel A. Ward
2019	J	`jnl`	Global Convergence of Adaptive Gradient Methods for An Over-parameterized Neural Network. CoRR Xiaoxia Wu, Simon S. Du, Rachel A. Ward
2019	J	`jnl`	Implicit Regularization of Normalization Methods. CoRR Xiaoxia Wu, Edgar Dobriban, Tongzheng Ren, Shanshan Wu, Zhiyuan Li, Suriya Gunasekar, Rachel A. Ward, Qiang Liu
2019	J	`jnl`	Linear Convergence of Adaptive Stochastic Gradient Descent. CoRR Yuege Xie, Xiaoxia Wu, Rachel A. Ward
2018	J	`jnl`	AdaGrad stepsizes: Sharp convergence over nonconvex landscapes, from any initialization. CoRR Rachel A. Ward, Xiaoxia Wu, Léon Bottou
2018	J	`jnl`	Extracting Sparse High-Dimensional Dynamics from Limited Data. SIAM J. Appl. Math. Hayden Schaeffer, Giang Tran, Rachel A. Ward
2018	J	`jnl`	Extracting structured dynamical systems using sparse optimization with very few samples. CoRR Hayden Schaeffer, Giang Tran, Rachel A. Ward, Linan Zhang
2018	J	`jnl`	Greedy Variance Estimation for the LASSO. CoRR Christopher Kennedy, Rachel A. Ward
2018	J	`jnl`	Recovery guarantees for polynomial approximation from dependent data with outliers. CoRR Lam Si Tung Ho, Hayden Schaeffer, Giang Tran, Rachel A. Ward
2018	J	`jnl`	WNGrad: Learn the Learning Rate in Gradient Descent. CoRR Xiaoxia Wu, Rachel A. Ward, Léon Bottou
2017	J	`jnl`	Exact Recovery of Chaotic Systems from Highly Corrupted Data. Multiscale Model. Simul. Giang Tran, Rachel A. Ward
2017	A	`conf`	Fast Cross-Polytope Locality-Sensitive Hashing. ITCS Christopher Kennedy, Rachel A. Ward
2017	Misc	`conf`	Learning the second-moment matrix of a smooth function from point samples. ACSSC Armin Eftekhari, Michael B. Wakin, Ping Li, Paul G. Constantine, Rachel A. Ward
2016	J	`jnl`	A polynomial-time relaxation of the Gromov-Hausdorff distance. CoRR Soledad Villar, Afonso S. Bandeira, Andrew J. Blumberg, Rachel A. Ward
2016	J	`jnl`	Batched Stochastic Gradient Descent with Weighted Sampling. CoRR Deanna Needell, Rachel A. Ward
2016	J	`jnl`	Clustering subgaussian mixtures by semidefinite programming. CoRR Dustin G. Mixon, Soledad Villar, Rachel A. Ward
2016	B	`conf`	Clustering subgaussian mixtures with k-means. ITW Dustin G. Mixon, Soledad Villar, Rachel A. Ward
2016	J	`jnl`	Fast Cross-Polytope Locality-Sensitive Hashing. CoRR Christopher Kennedy, Rachel A. Ward
2016	J	`jnl`	Improved bounds for sparse recovery from subsampled random convolutions. CoRR Shahar Mendelson, Holger Rauhut, Rachel A. Ward
2016	J	`jnl`	Learning the Differential Correlation Matrix of a Smooth Function From Point Samples. CoRR Armin Eftekhari, Ping Li, Michael B. Wakin, Rachel A. Ward
2016	J	`jnl`	MC^2: A Two-Phase Algorithm for Leveraged Matrix Completion. CoRR Armin Eftekhari, Michael B. Wakin, Rachel A. Ward
2016	J	`jnl`	One-Bit Compressive Sensing With Norm Estimation. IEEE Trans. Inf. Theory Karin Knudson, Rayan Saab, Rachel A. Ward
2016	J	`jnl`	Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm. Math. Program. Deanna Needell, Nathan Srebro, Rachel A. Ward
2016	J	`jnl`	The Sample Complexity of Weighted Sparse Approximation. IEEE Trans. Signal Process. Bubacarr Bah, Rachel A. Ward
2015	J	`jnl`	Completing any low-rank matrix, provably. J. Mach. Learn. Res. Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel A. Ward
2015	J	`jnl`	Compressive Sensing with Redundant Dictionaries and Structured Measurements. CoRR Felix Krahmer, Deanna Needell, Rachel A. Ward
2015	J	`jnl`	Compressive Sensing with Redundant Dictionaries and Structured Measurements. SIAM J. Math. Anal. Felix Krahmer, Deanna Needell, Rachel A. Ward
2015	J	`jnl`	Recovery guarantees for exemplar-based clustering. Inf. Comput. Abhinav Nellore, Rachel A. Ward
2015	A	`conf`	Relax, No Need to Round: Integrality of Clustering Formulations. ITCS Pranjal Awasthi, Afonso S. Bandeira, Moses Charikar, Ravishankar Krishnaswamy, Soledad Villar, Rachel A. Ward
2015	J	`jnl`	The sample complexity of weighted sparse approximation. CoRR Bubacarr Bah, Rachel A. Ward
2014	J	`jnl`	A unified framework for linear dimensionality reduction in l CoRR Rachel A. Ward
2014	A*	`conf`	Coherent Matrix Completion. ICML Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel A. Ward
2014	J	`jnl`	Relax, no need to round: integrality of clustering formulations. CoRR Pranjal Awasthi, Afonso S. Bandeira, Moses Charikar, Ravishankar Krishnaswamy, Soledad Villar, Rachel A. Ward
2014	J	`jnl`	Stable and Robust Sampling Strategies for Compressive Imaging. IEEE Trans. Image Process. Felix Krahmer, Rachel A. Ward
2014	—	`conf`	Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm. NIPS Deanna Needell, Rachel A. Ward, Nathan Srebro
2013	J	`jnl`	A Symbol-Based Algorithm for Decoding Bar Codes. SIAM J. Imaging Sci. Mark A. Iwen, Fadil Santosa, Rachel A. Ward
2013	J	`jnl`	Coherent Matrix Completion. CoRR Srinadh Bhojanapalli, Yudong Chen, Sujay Sanghavi, Rachel A. Ward
2013	J	`jnl`	Near-Optimal Compressed Sensing Guarantees for Total Variation Minimization. IEEE Trans. Image Process. Deanna Needell, Rachel A. Ward
2013	J	`jnl`	Recovery guarantees for exemplar-based clustering. CoRR Abhinav Nellore, Rachel A. Ward
2013	J	`jnl`	Stable Image Reconstruction Using Total Variation Minimization. SIAM J. Imaging Sci. Deanna Needell, Rachel A. Ward
2013	J	`jnl`	Stochastic gradient descent and the randomized Kaczmarz algorithm. CoRR Deanna Needell, Nathan Srebro, Rachel A. Ward
2012	J	`jnl`	A symbol-based algorithm for decoding bar codes CoRR Mark A. Iwen, Fadil Santosa, Rachel A. Ward
2012	J	`jnl`	Compressive imaging: stable and robust recovery from variable density frequency samples CoRR Felix Krahmer, Rachel A. Ward
2012	J	`jnl`	Root-Exponential Accuracy for Coarse Quantization of Finite Frame Expansions. IEEE Trans. Inf. Theory Felix Krahmer, Rayan Saab, Rachel A. Ward
2012	J	`jnl`	Sparse Legendre expansions via l J. Approx. Theory Holger Rauhut, Rachel A. Ward
2012	J	`jnl`	Stable image reconstruction using total variation minimization CoRR Deanna Needell, Rachel A. Ward
2012	J	`jnl`	Total variation minimization for stable multidimensional signal recovery CoRR Deanna Needell, Rachel A. Ward
2012	J	`jnl`	Weighted Eigenfunction Estimates with Applications to Compressed Sensing. SIAM J. Math. Anal. Nicolas Burq, Semyon Dyatlov, Rachel A. Ward, Maciej Zworski
2011	J	`jnl`	Computing the confidence levels for a root-mean-square test of goodness-of-fit. Appl. Math. Comput. William Perkins, Mark Tygert, Rachel A. Ward
2011	J	`jnl`	Low-rank Matrix Recovery via Iteratively Reweighted Least Squares Minimization. SIAM J. Optim. Massimo Fornasier, Holger Rauhut, Rachel A. Ward
2011	J	`jnl`	New and Improved Johnson-Lindenstrauss Embeddings via the Restricted Isometry Property. SIAM J. Math. Anal. Felix Krahmer, Rachel A. Ward
2011	A*	`conf`	This is your brain on interfaces: enhancing usability testing with functional near-infrared spectroscopy. CHI Leanne M. Hirshfield, Rebecca Gulotta, Stuart H. Hirshfield, Samuel W. Hincks, Matthew Russell, Rachel A. Ward, Tom Williams, Robert J. K. Jacob
2011	—	`conf`	Trust in Human-Computer Interactions as Measured by Frustration, Surprise, and Workload. HCI (20) Leanne M. Hirshfield, Stuart H. Hirshfield, Samuel W. Hincks, Matthew Russell, Rachel A. Ward, Tom Williams
2010	Misc	`conf`	Efficient and stable recovery of Legendre-sparse polynomials. CISS Holger Rauhut, Rachel A. Ward
2010	J	`jnl`	Iterative Thresholding Meets Free-Discontinuity Problems. Found. Comput. Math. Massimo Fornasier, Rachel A. Ward
2010	J	`jnl`	Lower bounds for the error decay incurred by coarse quantization schemes CoRR Felix Krahmer, Rachel A. Ward
2010	J	`jnl`	New and improved Johnson-Lindenstrauss embeddings via the Restricted Isometry Property CoRR Felix Krahmer, Rachel A. Ward
2010	J	`jnl`	On the Complexity of Mumford-Shah-Type Regularization, Viewed as a Relaxed Sparsity Constraint. IEEE Trans. Image Process. Boris Alexeev, Rachel A. Ward
2009	J	`jnl`	Compressed sensing with cross validation. IEEE Trans. Inf. Theory Rachel A. Ward
2009	J	`jnl`	Shape deformation in continuous map generalization. GeoInformatica Jeff Danciger, Satyan L. Devadoss, John Mugno, Don Sheehy, Rachel A. Ward