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ORCIDJarvis D. Haupt
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- affiliation: University of Minnesota - Twin Cities, Department of Electrical and Computer Engineering
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2020 – today
- 2024
[j18]Akshay Kumar, Jarvis D. Haupt:
Directional Convergence Near Small Initializations and Saddles in Two-Homogeneous Neural Networks. Trans. Mach. Learn. Res. 2024 (2024)- [i33]Akshay Kumar, Jarvis D. Haupt:
Directional Convergence Near Small Initializations and Saddles in Two-Homogeneous Neural Networks. CoRR abs/2402.09226 (2024) - [i32]Akshay Kumar, Jarvis D. Haupt:
Early Directional Convergence in Deep Homogeneous Neural Networks for Small Initializations. CoRR abs/2403.08121 (2024) - 2021
- [j17]Jineng Ren, Jarvis D. Haupt, Zehua Guo:
Communication-efficient hierarchical distributed optimization for multi-agent policy evaluation. J. Comput. Sci. 49: 101280 (2021) - [j16]Alex Gutierrez, Michael Mullen
, Di Xiao, Albert Jang, Taylor Froelich, Michael Garwood, Jarvis D. Haupt:
Reducing the Complexity of Model-Based MRI Reconstructions via Sparsification. IEEE Trans. Medical Imaging 40(9): 2477-2486 (2021) - 2020
- [j15]Akshay Kumar, Jarvis D. Haupt:
Convexifying Sparse Interpolation With Infinitely Wide Neural Networks: An Atomic Norm Approach. IEEE Signal Process. Lett. 27: 2114-2118 (2020) - [j14]Sirisha Rambhatla, Xingguo Li, Jineng Ren, Jarvis D. Haupt:
A Dictionary-Based Generalization of Robust PCA With Applications to Target Localization in Hyperspectral Imaging. IEEE Trans. Signal Process. 68: 1760-1775 (2020) - [j13]Jineng Ren, Jarvis D. Haupt:
A Provably Communication-Efficient Asynchronous Distributed Inference Method for Convex and Nonconvex Problems. IEEE Trans. Signal Process. 68: 3325-3340 (2020) - [c57]Sirisha Rambhatla, Xingguo Li, Jarvis D. Haupt:
Provable Online CP/PARAFAC Decomposition of a Structured Tensor via Dictionary Learning. NeurIPS 2020 - [i31]Sirisha Rambhatla, Xingguo Li, Jarvis D. Haupt:
Provable Online CP/PARAFAC Decomposition of a Structured Tensor via Dictionary Learning. CoRR abs/2006.16442 (2020) - [i30]Akshay Kumar, Jarvis D. Haupt:
Convexifying Sparse Interpolation with Infinitely Wide Neural Networks: An Atomic Norm Approach. CoRR abs/2007.08009 (2020)
2010 – 2019
- 2019
- [j12]Xingguo Li, Junwei Lu, Raman Arora, Jarvis D. Haupt, Han Liu, Zhaoran Wang, Tuo Zhao:
Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization. IEEE Trans. Inf. Theory 65(6): 3489-3514 (2019) - [c56]Xingguo Li, Jarvis D. Haupt:
Sketching Dictionary Based Robust PCA in Large Matrices. ACSSC 2019: 702-706 - [c55]Abhinav V. Sambasivan, Richard G. Paxman, Jarvis D. Haupt:
Computer Graphics meets Estimation Theory: Parameter Estimation Lower Bounds for Plenoptic Imaging Systems. ACSSC 2019: 1021-1025 - [c54]Zhehui Chen, Xingguo Li, Lin Yang, Jarvis D. Haupt, Tuo Zhao:
On Constrained Nonconvex Stochastic Optimization: A Case Study for Generalized Eigenvalue Decomposition. AISTATS 2019: 916-925 - [c53]Sirisha Rambhatla, Xingguo Li, Jarvis D. Haupt:
NOODL: Provable Online Dictionary Learning and Sparse Coding. ICLR (Poster) 2019 - [c52]Xingguo Li, Haoming Jiang, Jarvis D. Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao:
On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss Function. UAI 2019: 49-59 - [i29]Sirisha Rambhatla, Xingguo Li, Jarvis D. Haupt:
A Dictionary Based Generalization of Robust PCA. CoRR abs/1902.08171 (2019) - [i28]Sirisha Rambhatla, Xingguo Li, Jineng Ren, Jarvis D. Haupt:
A Dictionary-Based Generalization of Robust PCA Part I: Study of Theoretical Properties. CoRR abs/1902.08304 (2019) - [i27]Sirisha Rambhatla, Nikos D. Sidiropoulos, Jarvis D. Haupt:
TensorMap: Lidar-Based Topological Mapping and Localization via Tensor Decompositions. CoRR abs/1902.10226 (2019) - [i26]Sirisha Rambhatla, Xingguo Li, Jineng Ren, Jarvis D. Haupt:
A Dictionary-Based Generalization of Robust PCA Part II: Applications to Hyperspectral Demixing. CoRR abs/1902.10238 (2019) - [i25]Sirisha Rambhatla, Xingguo Li, Jarvis D. Haupt:
Target-based Hyperspectral Demixing via Generalized Robust PCA. CoRR abs/1902.11111 (2019) - [i24]Sirisha Rambhatla, Xingguo Li, Jarvis D. Haupt:
NOODL: Provable Online Dictionary Learning and Sparse Coding. CoRR abs/1902.11261 (2019) - [i23]Jineng Ren, Jarvis D. Haupt:
A Provably Communication-Efficient Asynchronous Distributed Inference Method for Convex and Nonconvex Problems. CoRR abs/1903.06871 (2019) - 2018
- [j11]Abhinav V. Sambasivan, Jarvis D. Haupt:
Minimax Lower Bounds for Noisy Matrix Completion Under Sparse Factor Models. IEEE Trans. Inf. Theory 64(5): 3274-3285 (2018) - [c51]Meng Ma, Jineng Ren, Georgios B. Giannakis, Jarvis D. Haupt:
Fast Asynchronous Decentralized Optimization: Allowing Multiple Masters. GlobalSIP 2018: 633-637 - [c50]Jineng Ren, Jarvis D. Haupt:
Provably Communication-Efficient Asynchronous Distributed Inference for Convex and Nonconvex Problems. GlobalSIP 2018: 638-642 - [c49]Sijia Liu, Xingguo Li, Pin-Yu Chen, Jarvis D. Haupt, Lisa Amini:
Zeroth-Order Stochastic Projected Gradient Descent for Nonconvex Optimization. GlobalSIP 2018: 1179-1183 - [c48]Sirisha Rambhatla, Nikos D. Sidiropoulos, Jarvis D. Haupt:
TensorMap: LIDAR-Based Topological Mapping and Localization via Tensor Decompositions. GlobalSIP 2018: 1368-1372 - [c47]Xingguo Li, Jineng Ren, Sirisha Rambhatla, Yangyang Xu, Jarvis D. Haupt:
Robust PCA via Dictionary Based Outlier Pursuit. ICASSP 2018: 4699-4703 - [c46]Xingguo Li, Jarvis D. Haupt, Junwei Lu, Zhaoran Wang, Raman Arora, Han Liu, Tuo Zhao:
Symmetry. Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization. ITA 2018: 1-9 - [i22]Zhehui Chen, Xingguo Li, Lin F. Yang, Jarvis D. Haupt, Tuo Zhao:
On Landscape of Lagrangian Functions and Stochastic Search for Constrained Nonconvex Optimization. CoRR abs/1806.05151 (2018) - [i21]Xingguo Li, Junwei Lu, Zhaoran Wang, Jarvis D. Haupt, Tuo Zhao:
On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond. CoRR abs/1806.05159 (2018) - 2017
- [j10]Swayambhoo Jain, Urvashi Oswal, Kevin S. Xu, Brian Eriksson, Jarvis D. Haupt:
A Compressed Sensing Based Decomposition of Electrodermal Activity Signals. IEEE Trans. Biomed. Eng. 64(9): 2142-2151 (2017) - [c45]Sirisha Rambhatla, Xingguo Li, Jarvis D. Haupt:
Target-based hyperspectral demixing via generalized robust PCA. ACSSC 2017: 420-424 - [c44]Xingguo Li, Jarvis D. Haupt:
Robust Low-Complexity methods for matrix column outlier identification. CAMSAP 2017: 1-5 - [c43]Jineng Ren, Xingguo Li, Jarvis D. Haupt:
Communication-Efficient distributed optimization for sparse learning via two-way truncation. CAMSAP 2017: 1-5 - [c42]Mojtaba Kadkhodaie Elyaderani, Swayambhoo Jain, Jeffrey M. Druce, Stefano Gonella, Jarvis D. Haupt:
Group-level support recovery guarantees for group lasso estimator. ICASSP 2017: 4366-4370 - [c41]Swayambhoo Jain, Jarvis D. Haupt:
Convolutional approximations to linear dimensionality reduction operators. ICASSP 2017: 5885-5889 - [c40]Swayambhoo Jain, Alexander Gutierrez, Jarvis D. Haupt:
Noisy tensor completion for tensors with a sparse canonical polyadic factor. ISIT 2017: 2153-2157 - [c39]Xingguo Li, Lin Yang, Jason Ge, Jarvis D. Haupt, Tong Zhang, Tuo Zhao:
On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning. NIPS 2017: 2742-2752 - [c38]Xingguo Li, Jarvis D. Haupt, David P. Woodruff:
Near Optimal Sketching of Low-Rank Tensor Regression. NIPS 2017: 3466-3476 - [i20]Xingguo Li, Lin F. Yang, Jason Ge, Jarvis D. Haupt, Tong Zhang, Tuo Zhao:
On Quadratic Convergence of DC Proximal Newton Algorithm for Nonconvex Sparse Learning in High Dimensions. CoRR abs/1706.06066 (2017) - [i19]Mojtaba Kadkhodaie Elyaderani, Swayambhoo Jain, Jeffrey M. Druce, Stefano Gonella, Jarvis D. Haupt:
Improved Support Recovery Guarantees for the Group Lasso With Applications to Structural Health Monitoring. CoRR abs/1708.08826 (2017) - [i18]Jineng Ren, Jarvis D. Haupt:
Communication-efficient Algorithm for Distributed Sparse Learning via Two-way Truncation. CoRR abs/1709.00537 (2017) - [i17]Jarvis D. Haupt, Xingguo Li, David P. Woodruff:
Near Optimal Sketching of Low-Rank Tensor Regression. CoRR abs/1709.07093 (2017) - 2016
- [j9]Akshay Soni, Swayambhoo Jain, Jarvis D. Haupt, Stefano Gonella:
Noisy Matrix Completion Under Sparse Factor Models. IEEE Trans. Inf. Theory 62(6): 3636-3661 (2016) - [c37]Jineng Ren, Xingguo Li, Jarvis D. Haupt:
Robust PCA via tensor outlier pursuit. ACSSC 2016: 1744-1749 - [c36]Sirisha Rambhatla, Xingguo Li, Jarvis D. Haupt:
A dictionary based generalization of robust PCA. GlobalSIP 2016: 1315-1319 - [c35]Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis D. Haupt:
Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning. ICML 2016: 917-925 - [c34]Xingguo Li, Jarvis D. Haupt:
A refined analysis for the sample complexity of adaptive compressive outlier sensing. SSP 2016: 1-5 - [i16]Swayambhoo Jain, Urvashi Oswal, Kevin S. Xu, Brian Eriksson, Jarvis D. Haupt:
A Compressed Sensing Based Decomposition of Electrodermal Activity Signals. CoRR abs/1602.07754 (2016) - [i15]Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis D. Haupt:
Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning. CoRR abs/1605.02711 (2016) - [i14]Xingguo Li, Jarvis D. Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao:
A First Order Free Lunch for SQRT-Lasso. CoRR abs/1605.07950 (2016) - [i13]Xingguo Li, Jarvis D. Haupt:
Robust Low-Complexity Randomized Methods for Locating Outliers in Large Matrices. CoRR abs/1612.02334 (2016) - [i12]Xingguo Li, Zhaoran Wang, Junwei Lu, Raman Arora, Jarvis D. Haupt, Han Liu, Tuo Zhao:
Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization. CoRR abs/1612.09296 (2016) - 2015
- [j8]Xingguo Li, Jarvis D. Haupt:
Identifying Outliers in Large Matrices via Randomized Adaptive Compressive Sampling. IEEE Trans. Signal Process. 63(7): 1792-1807 (2015) - [c33]Mojtaba Kadkhodaie, Swayambhoo Jain, Jarvis D. Haupt, Jeffrey M. Druce, Stefano Gonella:
Locating rare and weak material anomalies by convex demixing of propagating wavefields. CAMSAP 2015: 373-376 - [c32]Xingguo Li, Jarvis D. Haupt:
Locating salient group-structured image features via adaptive compressive sensing. GlobalSIP 2015: 393-397 - [c31]Ilija Bogunovic, Volkan Cevher, Jarvis D. Haupt, Jonathan Scarlett:
Active learning of self-concordant like multi-index functions. ICASSP 2015: 2189-2193 - [c30]Xingguo Li, Jarvis D. Haupt:
Outlier identification via randomized adaptive compressive sampling. ICASSP 2015: 3302-3306 - [i11]Abhinav V. Sambasivan, Jarvis D. Haupt:
Minimax Lower Bounds for Noisy Matrix Completion Under Sparse Factor Models. CoRR abs/1510.00701 (2015) - 2014
- [j7]Akshay Soni, Jarvis D. Haupt:
On the Fundamental Limits of Recovering Tree Sparse Vectors From Noisy Linear Measurements. IEEE Trans. Inf. Theory 60(1): 133-149 (2014) - [c29]Akshay Soni, Swayambhoo Jain, Jarvis D. Haupt, Stefano Gonella:
Error bounds for maximum likelihood matrix completion under sparse factor models. GlobalSIP 2014: 399-403 - [c28]Akshay Soni, Jarvis D. Haupt, Fatih Porikli:
Recycled linear classifiers for multiclass classification. ICASSP 2014: 2957-2961 - [c27]Jarvis D. Haupt, Nikos D. Sidiropoulos, Georgios B. Giannakis:
Sparse dictionary learning from 1-BIT data. ICASSP 2014: 7664-7668 - [c26]Akshay Soni, Jarvis D. Haupt:
Estimation error guarantees for Poisson denoising with sparse and structured dictionary models. ISIT 2014: 2002-2006 - [i10]Jeffrey M. Druce, Jarvis D. Haupt, Stefano Gonella:
Anomaly-Sensitive Dictionary Learning for Unsupervised Diagnostics of Solid Media. CoRR abs/1405.2496 (2014) - [i9]Xingguo Li, Jarvis D. Haupt:
Identifying Outliers in Large Matrices via Randomized Adaptive Compressive Sampling. CoRR abs/1407.0312 (2014) - [i8]Akshay Soni, Swayambhoo Jain, Jarvis D. Haupt, Stefano Gonella:
Noisy Matrix Completion under Sparse Factor Models. CoRR abs/1411.0282 (2014) - 2013
- [c25]Swayambhoo Jain, Akshay Soni, Jarvis D. Haupt:
Compressive measurement designs for estimating structured signals in structured clutter: A Bayesian Experimental Design approach. ACSSC 2013: 163-167 - [c24]Sirisha Rambhatla, Jarvis D. Haupt:
Semi-blind source separation via sparse representations and online dictionary learning. ACSSC 2013: 1687-1691 - [c23]Jarvis D. Haupt:
Locating salient items in large data collections with compressive linear measurements. CAMSAP 2013: 9-12 - [c22]Akshay Soni, Jarvis D. Haupt:
Fundamental limits for support recovery of tree-sparse signals from noisy compressive samples. GlobalSIP 2013: 961-964 - [i7]Akshay Soni, Jarvis D. Haupt:
On the Fundamental Limits of Recovering Tree Sparse Vectors from Noisy Linear Measurements. CoRR abs/1306.4391 (2013) - [i6]Stefano Gonella, Jarvis D. Haupt:
Automated Defect Localization via Low Rank Plus Outlier Modeling of Propagating Wavefield Data. CoRR abs/1307.5102 (2013) - [i5]Swayambhoo Jain, Akshay Soni, Jarvis D. Haupt:
Compressive Measurement Designs for Estimating Structured Signals in Structured Clutter: A Bayesian Experimental Design Approach. CoRR abs/1311.5599 (2013) - 2012
- [c21]Akshay Soni, Jarvis D. Haupt:
Learning sparse representations for adaptive compressive sensing. ICASSP 2012: 2097-2100 - [c20]Akshay Soni, Jarvis D. Haupt:
Level set estimation from compressive measurements using box constrained total variation regularization. ICIP 2012: 2573-2576 - [c19]Jarvis D. Haupt, Richard G. Baraniuk, Rui M. Castro, Robert D. Nowak:
Sequentially designed compressed sensing. SSP 2012: 401-404 - [p1]Jarvis D. Haupt, Robert D. Nowak:
Adaptive sensing for sparse recovery. Compressed Sensing 2012: 269-304 - [i4]Akshay Soni, Jarvis D. Haupt:
Level Set Estimation from Compressive Measurements using Box Constrained Total Variation Regularization. CoRR abs/1210.2474 (2012) - [i3]Sirisha Rambhatla, Jarvis D. Haupt:
Semi-blind Source Separation via Sparse Representations and Online Dictionary Learning. CoRR abs/1212.0451 (2012) - 2011
- [j6]Jarvis D. Haupt, Rui M. Castro, Robert D. Nowak:
Distilled Sensing: Adaptive Sampling for Sparse Detection and Estimation. IEEE Trans. Inf. Theory 57(9): 6222-6235 (2011) - [c18]Jarvis D. Haupt:
Session MP4a: Compressive sensing applications in networking. ACSCC 2011: 401-402 - [c17]Jarvis D. Haupt:
Session TA8b3: Adaptive sensing. ACSCC 2011: 1232-1234 - [c16]Akshay Soni, Jarvis D. Haupt:
Efficient adaptive compressive sensing using sparse hierarchical learned dictionaries. ACSCC 2011: 1250-1254 - [c15]Jarvis D. Haupt, Richard G. Baraniuk:
Robust support recovery using sparse compressive sensing matrices. CISS 2011: 1-6 - [c14]Lorne Applebaum, Waheed U. Bajwa, A. Robert Calderbank, Jarvis D. Haupt, Robert Nowak:
Deterministic pilot sequences for sparse channel estimation in OFDM systems. DSP 2011: 1-7 - [i2]Akshay Soni, Jarvis D. Haupt:
Efficient Adaptive Compressive Sensing Using Sparse Hierarchical Learned Dictionaries. CoRR abs/1111.6923 (2011) - 2010
- [j5]Waheed Uz Zaman Bajwa, Jarvis D. Haupt, Akbar M. Sayeed, Robert D. Nowak:
Compressed Channel Sensing: A New Approach to Estimating Sparse Multipath Channels. Proc. IEEE 98(6): 1058-1076 (2010) - [j4]Jarvis D. Haupt, Waheed Uz Zaman Bajwa, Gil M. Raz, Robert D. Nowak:
Toeplitz Compressed Sensing Matrices With Applications to Sparse Channel Estimation. IEEE Trans. Inf. Theory 56(11): 5862-5875 (2010) - [c13]Jarvis D. Haupt, Lorne Applebaum, Robert D. Nowak:
On the Restricted Isometry of deterministically subsampled Fourier matrices. CISS 2010: 1-6 - [c12]Jarvis D. Haupt, Rui M. Castro, Robert D. Nowak:
Improved bounds for sparse recovery from adaptive measurements. ISIT 2010: 1563-1567 - [i1]Jarvis D. Haupt, Rui M. Castro, Robert D. Nowak:
Distilled Sensing: Adaptive Sampling for Sparse Detection and Estimation. CoRR abs/1001.5311 (2010)
2000 – 2009
- 2009
- [c11]Jarvis D. Haupt, Rui M. Castro, Robert D. Nowak:
Distilled sensing: selective sampling for sparse signal recovery. AISTATS 2009: 216-223 - 2008
- [j3]Jarvis D. Haupt, Waheed U. Bajwa, Michael G. Rabbat, Robert D. Nowak:
Compressed Sensing for Networked Data. IEEE Signal Process. Mag. 25(2): 92-101 (2008) - [c10]Jarvis D. Haupt, Rui M. Castro, Robert D. Nowak:
Adaptive discovery of sparse signals in noise. ACSCC 2008: 1727-1731 - [c9]Waheed Uz Zaman Bajwa, Jarvis D. Haupt, Gil M. Raz, Robert D. Nowak:
Compressed channel sensing. CISS 2008: 5-10 - [c8]Rui M. Castro, Jarvis D. Haupt, Robert D. Nowak, Gil M. Raz:
Finding needles in noisy haystacks. ICASSP 2008: 5133-5136 - 2007
- [j2]Waheed Uz Zaman Bajwa, Jarvis D. Haupt, Akbar M. Sayeed, Robert D. Nowak:
Joint Source-Channel Communication for Distributed Estimation in Sensor Networks. IEEE Trans. Inf. Theory 53(10): 3629-3653 (2007) - [c7]Jarvis D. Haupt, Robert D. Nowak:
Compressive Sampling for Signal Detection. ICASSP (3) 2007: 1509-1512 - 2006
- [j1]Jarvis D. Haupt, Robert D. Nowak:
Signal Reconstruction From Noisy Random Projections. IEEE Trans. Inf. Theory 52(9): 4036-4048 (2006) - [c6]Jarvis D. Haupt, Rui M. Castro, Robert D. Nowak:
Compressed sensing in noisy imaging environments. Computational Imaging 2006: 606507 - [c5]Rui M. Castro, Jarvis D. Haupt, Robert D. Nowak:
Compressed Sensing Vs. Active Learning. ICASSP (3) 2006: 820-823 - [c4]Waheed Uz Zaman Bajwa, Jarvis D. Haupt, Akbar M. Sayeed, Robert D. Nowak:
A Universal Matched Source-Channel Communication Scheme for Wireless Sensor Ensembles. ICASSP (5) 2006: 1153-1156 - [c3]Jarvis D. Haupt, Robert D. Nowak:
Compressive Sampling Vs. Conventional Imaging. ICIP 2006: 1269-1272 - [c2]Michael G. Rabbat, Jarvis D. Haupt, Aarti Singh, Robert D. Nowak:
Decentralized compression and predistribution via randomized gossiping. IPSN 2006: 51-59 - [c1]Waheed Uz Zaman Bajwa, Jarvis D. Haupt, Akbar M. Sayeed, Robert D. Nowak:
Compressive wireless sensing. IPSN 2006: 134-142
Coauthor Index
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