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Raman Arora
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2020 – today
- 2024
- [c79]Michael Menart, Enayat Ullah, Raman Arora, Raef Bassily, Cristóbal Guzmán:
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates. ALT 2024: 868-906 - [c78]Thanh Nguyen-Tang, Raman Arora:
On The Statistical Complexity of Offline Decision-Making. ICML 2024 - [c77]Yunjuan Wang, Raman Arora:
Adversarially Robust Hypothesis Transfer Learning. ICML 2024 - [c76]Yunjuan Wang, Kaibo Zhang, Raman Arora:
Benign Overfitting in Adversarial Training of Neural Networks. ICML 2024 - [i46]Thanh Nguyen-Tang, Raman Arora
:
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling, and Beyond. CoRR abs/2401.03301 (2024) - [i45]Yunjuan Wang, Hussein Hazimeh, Natalia Ponomareva, Alexey Kurakin, Ibrahim Hammoud, Raman Arora
DART: A Principled Approach to Adversarially Robust Unsupervised Domain Adaptation. CoRR abs/2402.11120 (2024) - [i44]Enayat Ullah, Michael Menart, Raef Bassily, Cristóbal Guzmán, Raman Arora
Public-data Assisted Private Stochastic Optimization: Power and Limitations. CoRR abs/2403.03856 (2024) - [i43]Haque Ishfaq, Thanh Nguyen-Tang, Songtao Feng, Raman Arora, Mengdi Wang
Offline Multitask Representation Learning for Reinforcement Learning. CoRR abs/2403.11574 (2024) - [i42]Thanh Nguyen-Tang, Raman Arora:
Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms. CoRR abs/2411.00707 (2024) - 2023
- [j13]Enayat Ullah, Raman Arora:
Generalization bounds for Kernel Canonical Correlation Analysis. Trans. Mach. Learn. Res. 2023 (2023) - [j12]Enayat Ullah, Harry Lang, Raman Arora, Vladimir Braverman:
Clustering using Approximate Nearest Neighbour Oracles. Trans. Mach. Learn. Res. 2023 (2023) - [c75]Thanh Nguyen-Tang, Ming Yin, Sunil Gupta, Svetha Venkatesh, Raman Arora:
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation. AAAI 2023: 9310-9318 - [c74]Jared Markowitz, Ryan W. Gardner, Ashley J. Llorens, Raman Arora, I-Jeng Wang:
A Risk-Sensitive Approach to Policy Optimization. AAAI 2023: 15019-15027 - [c73]Thanh Nguyen-Tang, Raman Arora:
VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation. ICLR 2023 - [c72]Raman Arora, Raef Bassily, Tomás González, Cristóbal Guzmán, Michael Menart, Enayat Ullah:
Faster Rates of Convergence to Stationary Points in Differentially Private Optimization. ICML 2023: 1060-1092 - [c71]Enayat Ullah, Raman Arora:
From Adaptive Query Release to Machine Unlearning. ICML 2023: 34642-34667 - [c70]Anh Do, Thanh Nguyen-Tang, Raman Arora:
Multi-Agent Learning with Heterogeneous Linear Contextual Bandits. NeurIPS 2023 - [c69]Poorya Mianjy, Raman Arora:
Robustness Guarantees for Adversarially Trained Neural Networks. NeurIPS 2023 - [c68]Thanh Nguyen-Tang, Raman Arora:
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling and Beyond. NeurIPS 2023 - [c67]Austin Watkins, Enayat Ullah, Thanh Nguyen-Tang, Raman Arora:
Optimistic Rates for Multi-Task Representation Learning. NeurIPS 2023 - [i41]Thanh Nguyen-Tang, Raman Arora
Provably Efficient Neural Offline Reinforcement Learning via Perturbed Rewards. CoRR abs/2302.12780 (2023) - [i40]Enayat Ullah, Raman Arora:
From Adaptive Query Release to Machine Unlearning. CoRR abs/2307.11228 (2023) - [i39]Michael Menart, Enayat Ullah, Raman Arora
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates. CoRR abs/2311.13447 (2023) - 2022
- [j11]Amir Alipour-Fanid
Multiuser Scheduling in Centralized Cognitive Radio Networks: A Multi-Armed Bandit Approach. IEEE Trans. Cogn. Commun. Netw. 8(2): 1074-1091 (2022) - [c66]Raman Arora, Raef Bassily, Cristóbal Guzmán, Michael Menart, Enayat Ullah:
Differentially Private Generalized Linear Models Revisited. NeurIPS 2022 - [c65]Yunjuan Wang, Enayat Ullah, Poorya Mianjy, Raman Arora:
Adversarial Robustness is at Odds with Lazy Training. NeurIPS 2022 - [i38]Raman Arora
Differentially Private Generalized Linear Models Revisited. CoRR abs/2205.03014 (2022) - [i37]Raman Arora, Raef Bassily, Tomás González, Cristóbal Guzmán, Michael Menart, Enayat Ullah:
Faster Rates of Convergence to Stationary Points in Differentially Private Optimization. CoRR abs/2206.00846 (2022) - [i36]Yunjuan Wang, Enayat Ullah, Poorya Mianjy, Raman Arora
Adversarial Robustness is at Odds with Lazy Training. CoRR abs/2207.00411 (2022) - [i35]Jared Markowitz, Ryan W. Gardner, Ashley J. Llorens, Raman Arora
A Risk-Sensitive Approach to Policy Optimization. CoRR abs/2208.09106 (2022) - [i34]Thanh Nguyen-Tang, Ming Yin, Sunil Gupta, Svetha Venkatesh, Raman Arora
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation. CoRR abs/2211.13208 (2022) - 2021
- [c64]Jalaj Upadhyay, Sarvagya Upadhyay, Raman Arora:
Differentially Private Analysis on Graph Streams. AISTATS 2021: 1171-1179 - [c63]Raman Arora, Teodor Vanislavov Marinov, Mehryar Mohri:
Corralling Stochastic Bandit Algorithms. AISTATS 2021: 2116-2124 - [c62]Enayat Ullah, Tung Mai, Anup Rao, Ryan A. Rossi, Raman Arora:
Machine Unlearning via Algorithmic Stability. COLT 2021: 4126-4142 - [c61]Raman Arora, Peter L. Bartlett, Poorya Mianjy, Nathan Srebro:
Dropout: Explicit Forms and Capacity Control. ICML 2021: 351-361 - [c60]Yunjuan Wang, Poorya Mianjy, Raman Arora:
Robust Learning for Data Poisoning Attacks. ICML 2021: 10859-10869 - [i33]Enayat Ullah, Tung Mai, Anup Rao, Ryan A. Rossi, Raman Arora:
Machine Unlearning via Algorithmic Stability. CoRR abs/2102.13179 (2021) - 2020
- [j10]Lucia Specia, Loïc Barrault
Grounded Sequence to Sequence Transduction. IEEE J. Sel. Top. Signal Process. 14(3): 577-591 (2020) - [c59]Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, Raman Arora:
FetchSGD: Communication-Efficient Federated Learning with Sketching. ICML 2020: 8253-8265 - [c58]Poorya Mianjy, Raman Arora:
On Convergence and Generalization of Dropout Training. NeurIPS 2020 - [c57]Jeremias Sulam, Ramchandran Muthukumar, Raman Arora:
Adversarial Robustness of Supervised Sparse Coding. NeurIPS 2020 - [c56]Zhen Zhang, Chaokun Chang, Haibin Lin, Yida Wang, Raman Arora
Is Network the Bottleneck of Distributed Training? NetAI@SIGCOMM 2020: 8-13 - [i32]Raman Arora, Teodor V. Marinov, Enayat Ullah:
Private Stochastic Convex Optimization: Efficient Algorithms for Non-smooth Objectives. CoRR abs/2002.09609 (2020) - [i31]Raman Arora, Peter L. Bartlett, Poorya Mianjy, Nathan Srebro:
Dropout: Explicit Forms and Capacity Control. CoRR abs/2003.03397 (2020) - [i30]Raman Arora, Teodor V. Marinov, Mehryar Mohri:
Corralling Stochastic Bandit Algorithms. CoRR abs/2006.09255 (2020) - [i29]Zhen Zhang, Chaokun Chang, Haibin Lin, Yida Wang, Raman Arora, Xin Jin:
Is Network the Bottleneck of Distributed Training? CoRR abs/2006.10103 (2020) - [i28]Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, Raman Arora:
FetchSGD: Communication-Efficient Federated Learning with Sketching. CoRR abs/2007.07682 (2020) - [i27]Jeremias Sulam
Adversarial Robustness of Supervised Sparse Coding. CoRR abs/2010.12088 (2020) - [i26]Poorya Mianjy, Raman Arora:
On Convergence and Generalization of Dropout Training. CoRR abs/2010.12711 (2020)
2010 – 2019
- 2019
- [j9]Xingguo Li
Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization. IEEE Trans. Inf. Theory 65(6): 3489-3514 (2019) - [c55]Nils Holzenberger, Shruti Palaskar, Pranava Madhyastha
Learning from Multiview Correlations in Open-domain Videos. ICASSP 2019: 8628-8632 - [c54]Poorya Mianjy, Raman Arora:
On Dropout and Nuclear Norm Regularization. ICML 2019: 4575-4584 - [c53]Chris Paxton, Yotam Barnoy, Kapil D. Katyal, Raman Arora
Visual Robot Task Planning. ICRA 2019: 8832-8838 - [c52]Raman Arora, Teodor Vanislavov Marinov, Mehryar Mohri:
Bandits with Feedback Graphs and Switching Costs. NeurIPS 2019: 10397-10407 - [c51]Raman Arora, Teodor Vanislavov Marinov:
Efficient Convex Relaxations for Streaming PCA. NeurIPS 2019: 10496-10505 - [c50]Nikita Ivkin, Daniel Rothchild, Enayat Ullah, Vladimir Braverman, Ion Stoica, Raman Arora:
Communication-efficient Distributed SGD with Sketching. NeurIPS 2019: 13144-13154 - [c49]Raman Arora, Jalaj Upadhyay:
On Differentially Private Graph Sparsification and Applications. NeurIPS 2019: 13378-13389 - [c48]Adrian Benton, Huda Khayrallah, Biman Gujral, Dee Ann Reisinger, Sheng Zhang, Raman Arora:
Deep Generalized Canonical Correlation Analysis. RepL4NLP@ACL 2019: 1-6 - [c47]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 - [i25]Nikita Ivkin, Daniel Rothchild, Enayat Ullah, Vladimir Braverman, Ion Stoica, Raman Arora:
Communication-efficient distributed SGD with Sketching. CoRR abs/1903.04488 (2019) - [i24]Poorya Mianjy, Raman Arora:
On Dropout and Nuclear Norm Regularization. CoRR abs/1905.11887 (2019) - [i23]Raman Arora, Teodor V. Marinov, Mehryar Mohri:
Bandits with Feedback Graphs and Switching Costs. CoRR abs/1907.12189 (2019) - [i22]Nils Holzenberger, Raman Arora:
Multiview Representation Learning for a Union of Subspaces. CoRR abs/1912.12766 (2019) - 2018
- [j8]Juan Rafael Orozco-Arroyave
NeuroSpeech: An open-source software for Parkinson's speech analysis. Digit. Signal Process. 77: 207-221 (2018) - [j7]Juan Rafael Orozco-Arroyave, Juan Camilo Vásquez-Correa
NeuroSpeech. SoftwareX 8: 69-70 (2018) - [c46]Raman Arora, Amitabh Basu, Poorya Mianjy, Anirbit Mukherjee:
Understanding Deep Neural Networks with Rectified Linear Units. ICLR (Poster) 2018 - [c45]Teodor Vanislavov Marinov, Poorya Mianjy, Raman Arora:
Streaming Principal Component Analysis in Noisy Settings. ICML 2018: 3410-3419 - [c44]Poorya Mianjy, Raman Arora:
Stochastic PCA with 𝓁2 and 𝓁1 Regularization. ICML 2018: 3528-3536 - [c43]Poorya Mianjy, Raman Arora, René Vidal:
On the Implicit Bias of Dropout. ICML 2018: 3537-3545 - [c42]Xingguo Li, Jarvis D. Haupt, Junwei Lu, Zhaoran Wang, Raman Arora
Symmetry. Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization. ITA 2018: 1-9 - [c41]Raman Arora, Vladimir Braverman, Jalaj Upadhyay:
Differentially Private Robust Low-Rank Approximation. NeurIPS 2018: 4141-4149 - [c40]Lin F. Yang
The Physical Systems Behind Optimization Algorithms. NeurIPS 2018: 4377-4386 - [c39]Raman Arora, Michael Dinitz
Policy Regret in Repeated Games. NeurIPS 2018: 6733-6742 - [c38]Enayat Ullah, Poorya Mianjy, Teodor Vanislavov Marinov, Raman Arora:
Streaming Kernel PCA with \tilde{O}(\sqrt{n}) Random Features. NeurIPS 2018: 7322-7332 - [i21]Chris Paxton, Yotam Barnoy, Kapil D. Katyal, Raman Arora, Gregory D. Hager:
Visual Robot Task Planning. CoRR abs/1804.00062 (2018) - [i20]Poorya Mianjy, Raman Arora, René Vidal:
On the Implicit Bias of Dropout. CoRR abs/1806.09777 (2018) - [i19]Enayat Ullah, Poorya Mianjy, Teodor V. Marinov, Raman Arora:
Streaming Kernel PCA with Õ(√n) Random Features. CoRR abs/1808.00934 (2018) - [i18]Raman Arora, Michael Dinitz, Teodor V. Marinov, Mehryar Mohri:
Policy Regret in Repeated Games. CoRR abs/1811.04127 (2018) - [i17]Nils Holzenberger, Shruti Palaskar, Pranava Madhyastha, Florian Metze, Raman Arora:
Learning from Multiview Correlations in Open-Domain Videos. CoRR abs/1811.08890 (2018) - 2017
- [j6]Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong:
On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. J. Mach. Learn. Res. 18: 184:1-184:24 (2017) - [c37]Juan Camilo Vásquez-Correa
Multi-view representation learning via gcca for multimodal analysis of Parkinson's disease. ICASSP 2017: 2966-2970 - [c36]Milos Cernak, Elmar Nöth, Frank Rudzicz
On the impact of non-modal phonation on phonological features. ICASSP 2017: 5090-5094 - [c35]Leonardo Badino
A Speaker Adaptive DNN Training Approach for Speaker-Independent Acoustic Inversion. INTERSPEECH 2017: 984-988 - [c34]Raman Arora, Teodor Vanislavov Marinov, Poorya Mianjy, Nati Srebro:
Stochastic Approximation for Canonical Correlation Analysis. NIPS 2017: 4775-4784 - [i16]Adrian Benton, Huda Khayrallah, Biman Gujral, Dee Ann Reisinger, Sheng Zhang, Raman Arora:
Deep Generalized Canonical Correlation Analysis. CoRR abs/1702.02519 (2017) - [i15]Raman Arora, Teodor V. Marinov, Poorya Mianjy:
Stochastic Approximation for Canonical Correlation Analysis. CoRR abs/1702.06818 (2017) - [i14]Chris Paxton, Kapil D. Katyal, Christian Rupprecht, Raman Arora, Gregory D. Hager:
Learning to Imagine Manipulation Goals for Robot Task Planning. CoRR abs/1711.02783 (2017) - [i13]Raman Arora, Amitabh Basu, Poorya Mianjy, Anirbit Mukherjee:
Understanding Deep Neural Networks with Rectified Linear Units. Electron. Colloquium Comput. Complex. TR17 (2017) - 2016
- [c33]Adrian Benton, Raman Arora
Learning Multiview Embeddings of Twitter Users. ACL (2) 2016 - [c32]Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong:
An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. AISTATS 2016: 491-499 - [c31]Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis D. Haupt:
Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning. ICML 2016: 917-925 - [c30]Raman Arora, Poorya Mianjy, Teodor V. Marinov:
Stochastic Optimization for Multiview Representation Learning using Partial Least Squares. ICML 2016: 1786-1794 - [c29]Mo Yu, Mark Dredze, Raman Arora
Embedding Lexical Features via Low-Rank Tensors. HLT-NAACL 2016: 1019-1029 - [c28]Peter Schulam, Raman Arora:
Disease Trajectory Maps. NIPS 2016: 4709-4717 - [i12]Weiran Wang, Raman Arora, Karen Livescu, Jeff A. Bilmes:
On Deep Multi-View Representation Learning: Objectives and Optimization. CoRR abs/1602.01024 (2016) - [i11]Mo Yu, Mark Dredze, Raman Arora, Matthew R. Gormley:
Embedding Lexical Features via Low-Rank Tensors. CoRR abs/1604.00461 (2016) - [i10]Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis D. Haupt:
Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning. CoRR abs/1605.02711 (2016) - [i9]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) - [i8]Peter Schulam, Raman Arora:
Disease Trajectory Maps. CoRR abs/1606.09184 (2016) - [i7]Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong:
An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. CoRR abs/1607.02793 (2016) - [i6]Raman Arora, Amitabh Basu, Poorya Mianjy, Anirbit Mukherjee:
Understanding Deep Neural Networks with Rectified Linear Units. CoRR abs/1611.01491 (2016) - [i5]Lin F. Yang, Raman Arora, Vladimir Braverman, Tuo Zhao:
The Physical Systems Behind Optimization Algorithms. CoRR abs/1612.02803 (2016) - [i4]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
- [c27]Weiran Wang, Raman Arora
Stochastic optimization for deep CCA via nonlinear orthogonal iterations. Allerton 2015: 688-695 - [c26]Weiran Wang, Raman Arora
Unsupervised learning of acoustic features via deep canonical correlation analysis. ICASSP 2015: 4590-4594 - [c25]Weiran Wang, Raman Arora, Karen Livescu, Jeff A. Bilmes:
On Deep Multi-View Representation Learning. ICML 2015: 1083-1092 - [c24]Pushpendre Rastogi, Benjamin Van Durme, Raman Arora
Multiview LSA: Representation Learning via Generalized CCA. HLT-NAACL 2015: 556-566 - [i3]Weiran Wang, Raman Arora, Karen Livescu, Nathan Srebro:
Stochastic Optimization for Deep CCA via Nonlinear Orthogonal Iterations. CoRR abs/1510.02054 (2015) - 2014
- [c23]John Goes, Teng Zhang, Raman Arora, Gilad Lerman:
Robust Stochastic Principal Component Analysis. AISTATS 2014: 266-274 - [c22]Raman Arora
Multi-view learning with supervision for transformed bottleneck features. ICASSP 2014: 2499-2503 - [c21]Tuo Zhao, Mo Yu, Yiming Wang, Raman Arora, Han Liu:
Accelerated Mini-batch Randomized Block Coordinate Descent Method. NIPS 2014: 3329-3337 - [c20]Weiran Wang, Raman Arora
Reconstruction of articulatory measurements with smoothed low-rank matrix completion. SLT 2014: 54-59 - 2013
- [j5]Raman Arora, Maya R. Gupta, Amol Kapila, Maryam Fazel:
Similarity-based clustering by left-stochastic matrix factorization. J. Mach. Learn. Res. 14(1): 1715-1746 (2013) - [c19]Raman Arora, Marina Meila:
Consensus Ranking with Signed Permutations. AISTATS 2013: 117-125 - [c18]Raman Arora
Multi-view CCA-based acoustic features for phonetic recognition across speakers and domains. ICASSP 2013: 7135-7139 - [c17]Galen Andrew, Raman Arora, Jeff A. Bilmes, Karen Livescu:
Deep Canonical Correlation Analysis. ICML (3) 2013: 1247-1255 - [c16]Raman Arora, Andrew Cotter, Nati Srebro:
Stochastic Optimization of PCA with Capped MSG. NIPS 2013: 1815-1823 - [i2]Raman Arora, Andrew Cotter, Nathan Srebro:
Stochastic Optimization of PCA with Capped MSG. CoRR abs/1307.1674 (2013) - 2012
- [j4]Eric K. Garcia, Raman Arora
Optimized Regression for Efficient Function Evaluation. IEEE Trans. Image Process. 21(9): 4128-4140 (2012) - [c15]Raman Arora
Stochastic optimization for PCA and PLS. Allerton Conference 2012: 861-868 - [c14]Ofer Dekel, Ambuj Tewari, Raman Arora:
Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret. ICML 2012 - [c13]Raman Arora, Karen Livescu:
Kernel CCA for multi-view learning of acoustic features using articulatory measurements. MLSLP 2012: 34-37 - [c12]Raman Arora, Ofer Dekel, Ambuj Tewari:
Deterministic MDPs with Adversarial Rewards and Bandit Feedback. UAI 2012: 93-101 - [i1]Raman Arora, Ofer Dekel, Ambuj Tewari:
Deterministic MDPs with Adversarial Rewards and Bandit Feedback. CoRR abs/1210.4843 (2012) - 2011
- [c11]Raman Arora, Maya R. Gupta:
Minimizing bearing bias in tracking by de-coupled rotation and translation estimates. FUSION 2011: 1-7 - [c10]Raman Arora, Maya R. Gupta, Amol Kapila, Maryam Fazel:
Clustering by Left-Stochastic Matrix Factorization. ICML 2011: 761-768 - 2010
- [j3]Raman Arora
Optimal estimation and detection in homogeneous spaces. IEEE Trans. Signal Process. 58(5): 2623-2635 (2010) - [c9]Raman Arora
Distributed curve matching in camera networks using projective joint invariant signatures. ICDSC 2010: 103-110 - [c8]Raman Arora
An Efficient and Stable Algorithm for Learning Rotations. ICPR 2010: 2993-2996
2000 – 2009
- 2009
- [c7]Raman Arora
Reconstructing latent periods in genome sequences with insertions and deletions. GENSiPS 2009: 1-4 - [c6]Raman Arora
Estimating correspondence between multiple cameras using joint invariants. ICASSP 2009: 805-808 - [c5]Raman Arora:
On Learning Rotations. NIPS 2009: 55-63 - 2008
- [j2]Raman Arora
Latent Periodicities in Genome Sequences. IEEE J. Sel. Top. Signal Process. 2(3): 332-342 (2008) - [c4]Raman Arora
Localizing time-varying periodicities in symbolic sequences. ICASSP 2008: 641-644 - [c3]Raman Arora
Spherical Wiener filter. ICIP 2008: 549-552 - [c2]Raman Arora
Navigation using a spherical camera. ICPR 2008: 1-4 - 2007
- [j1]Raman Arora
Adaptive Wavetable Oscillators. IEEE Trans. Signal Process. 55(9): 4382-4392 (2007) - [c1]William A. Sethares, Raman Arora
Equilibria of Adaptive Wavetable Oscillators with Applications to Beat Tracking. ICASSP (4) 2007: 1301-1304
Coauthor Index
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