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Rina Panigrahy
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2020 – today
- 2024
- [i35]Kulin Shah, Nishanth Dikkala, Xin Wang, Rina Panigrahy:
Causal Language Modeling Can Elicit Search and Reasoning Capabilities on Logic Puzzles. CoRR abs/2409.10502 (2024) - 2023
- [c74]Nishanth Dikkala, Nikhil Ghosh, Raghu Meka, Rina Panigrahy, Nikhil Vyas, Xin Wang:
On the Benefits of Learning to Route in Mixture-of-Experts Models. EMNLP 2023: 9376-9396 - [c73]Cenk Baykal, Dylan J. Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang:
Alternating Updates for Efficient Transformers. NeurIPS 2023 - [i34]Cenk Baykal, Dylan J. Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang:
Alternating Updates for Efficient Transformers. CoRR abs/2301.13310 (2023) - [i33]Cenk Baykal, Dylan J. Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang:
The Power of External Memory in Increasing Predictive Model Capacity. CoRR abs/2302.00003 (2023) - [i32]Yuanzhi Li, Raghu Meka, Rina Panigrahy, Kulin Shah:
Simple Mechanisms for Representing, Indexing and Manipulating Concepts. CoRR abs/2310.12143 (2023) - 2022
- [c72]Shaojin Ding, Weiran Wang, Ding Zhao, Tara N. Sainath, Yanzhang He, Robert David, Rami Botros, Xin Wang, Rina Panigrahy, Qiao Liang, Dongseong Hwang, Ian McGraw, Rohit Prabhavalkar, Trevor Strohman:
A Unified Cascaded Encoder ASR Model for Dynamic Model Sizes. INTERSPEECH 2022: 1706-1710 - [c71]Cenk Baykal, Nishanth Dikkala, Rina Panigrahy, Cyrus Rashtchian, Xin Wang:
A Theoretical View on Sparsely Activated Networks. NeurIPS 2022 - [c70]Nishanth Dikkala, Sankeerth Rao Karingula, Raghu Meka, Jelani Nelson, Rina Panigrahy, Xin Wang:
Sketching based Representations for Robust Image Classification with Provable Guarantees. NeurIPS 2022 - [i31]Shaojin Ding, Weiran Wang, Ding Zhao, Tara N. Sainath, Yanzhang He, Robert David, Rami Botros, Xin Wang, Rina Panigrahy, Qiao Liang, Dongseong Hwang, Ian McGraw, Rohit Prabhavalkar, Trevor Strohman:
A Unified Cascaded Encoder ASR Model for Dynamic Model Sizes. CoRR abs/2204.06164 (2022) - [i30]Cenk Baykal, Nishanth Dikkala, Rina Panigrahy, Cyrus Rashtchian, Xin Wang:
A Theoretical View on Sparsely Activated Networks. CoRR abs/2208.04461 (2022) - 2021
- [c69]Rina Panigrahy, Xin Wang, Manzil Zaheer:
Sketch based Memory for Neural Networks. AISTATS 2021: 3169-3177 - [c68]Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang:
One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks. ICLR 2021 - [i29]Nishanth Dikkala, Gal Kaplun, Rina Panigrahy:
For Manifold Learning, Deep Neural Networks can be Locality Sensitive Hash Functions. CoRR abs/2103.06875 (2021) - [i28]Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang:
One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks. CoRR abs/2103.15261 (2021) - [i27]Zihao Deng, Zee Fryer, Brendan Juba, Rina Panigrahy, Xin Wang:
Provable Hierarchical Lifelong Learning with a Sketch-based Modular Architecture. CoRR abs/2112.10919 (2021) - 2020
- [c67]Abhimanyu Das, Sreenivas Gollapudi, Ravi Kumar, Rina Panigrahy:
On the Learnability of Random Deep Networks. SODA 2020: 398-410 - [i26]Atish Agarwala, Abhimanyu Das, Rina Panigrahy, Qiuyi Zhang:
Learning the gravitational force law and other analytic functions. CoRR abs/2005.07724 (2020)
2010 – 2019
- 2019
- [c66]Badih Ghazi, Rina Panigrahy, Joshua R. Wang:
Recursive Sketches for Modular Deep Learning. ICML 2019: 2211-2220 - [c65]Ravi Kumar, Rina Panigrahy, Ali Rahimi, David P. Woodruff:
Faster Algorithms for Binary Matrix Factorization. ICML 2019: 3551-3559 - [i25]Surbhi Goel, Rina Panigrahy:
Learning Two layer Networks with Multinomial Activation and High Thresholds. CoRR abs/1903.09231 (2019) - [i24]Abhimanyu Das, Sreenivas Gollapudi, Ravi Kumar, Rina Panigrahy:
On the Learnability of Deep Random Networks. CoRR abs/1904.03866 (2019) - [i23]Badih Ghazi, Rina Panigrahy, Joshua R. Wang:
Recursive Sketches for Modular Deep Learning. CoRR abs/1905.12730 (2019) - [i22]Rina Panigrahy:
How does the Mind store Information? CoRR abs/1910.06718 (2019) - 2018
- [c64]Rina Panigrahy, Ali Rahimi, Sushant Sachdeva
, Qiuyi Zhang:
Convergence Results for Neural Networks via Electrodynamics. ITCS 2018: 22:1-22:19 - 2017
- [c63]Sreenivas Gollapudi, Ravi Kumar, Debmalya Panigrahi, Rina Panigrahy:
Partitioning Orders in Online Shopping Services. CIKM 2017: 1319-1328 - [c62]Flavio Chierichetti, Sreenivas Gollapudi, Ravi Kumar, Silvio Lattanzi, Rina Panigrahy, David P. Woodruff:
Algorithms for $\ell_p$ Low-Rank Approximation. ICML 2017: 806-814 - [i21]Qiuyi Zhang, Rina Panigrahy, Sushant Sachdeva:
Electron-Proton Dynamics in Deep Learning. CoRR abs/1702.00458 (2017) - [i20]Flavio Chierichetti, Sreenivas Gollapudi, Ravi Kumar, Silvio Lattanzi, Rina Panigrahy, David P. Woodruff:
Algorithms for $\ell_p$ Low Rank Approximation. CoRR abs/1705.06730 (2017) - 2015
- [c61]Rina Panigrahy, Preyas Popat:
Fractal Structures in Adversarial Prediction. ITCS 2015: 75-84 - 2014
- [c60]Alexandr Andoni, Rina Panigrahy, Gregory Valiant, Li Zhang:
Learning Polynomials with Neural Networks. ICML 2014: 1908-1916 - [c59]Alexandr Andoni, Rina Panigrahy, Gregory Valiant, Li Zhang:
Learning Sparse Polynomial Functions. SODA 2014: 500-510 - [c58]Rina Panigrahy, Preyas Popat:
Optimal amortized regret in every interval. UAI 2014: 663-671 - 2013
- [c57]Abhimanyu Das, Sreenivas Gollapudi, Rina Panigrahy, Mahyar Salek:
Debiasing social wisdom. KDD 2013: 500-508 - [c56]Rina Panigrahy:
Adversarial Prediction: Lossless Predictors and Fractal Like Adversaries. WALCOM 2013: 4 - [i19]Rina Panigrahy, Preyas Popat:
Fractal structures in Adversarial Prediction. CoRR abs/1304.7576 (2013) - [i18]Rina Panigrahy, Preyas Popat:
Optimal amortized regret in every interval. CoRR abs/1304.7577 (2013) - [i17]Alexandr Andoni, Rina Panigrahy:
A Differential Equations Approach to Optimizing Regret Trade-offs. CoRR abs/1305.1359 (2013) - [i16]Behnam Neyshabur, Rina Panigrahy:
Sparse Matrix Factorization. CoRR abs/1311.3315 (2013) - 2012
- [c55]Michael Kapralov, Rina Panigrahy:
NNS Lower Bounds via Metric Expansion for l ∞ and EMD. ICALP (1) 2012: 545-556 - [c54]Michael Kapralov
Spectral sparsification via random spanners. ITCS 2012: 393-398 - [c53]Anish Das Sarma, Sreenivas Gollapudi, Rina Panigrahy, Li Zhang:
Understanding cyclic trends in social choices. WSDM 2012: 593-602 - [c52]Rina Panigrahy, Marc Najork
How user behavior is related to social affinity. WSDM 2012: 713-722 - [i15]Rina Panigrahy, Li Zhang:
The Mind Grows Circuits. CoRR abs/1203.0088 (2012) - 2011
- [j16]Atish Das Sarma, Sreenivas Gollapudi, Rina Panigrahy:
Estimating PageRank on graph streams. J. ACM 58(3): 13:1-13:19 (2011) - [c51]Michael Kapralov, Rina Panigrahy:
Multiplicative Approximations of Random Walk Transition Probabilities. APPROX-RANDOM 2011: 266-276 - [c50]Michael Kapralov
Prediction strategies without loss. NIPS 2011: 828-836 - [c49]Yinglian Xie, Rina Panigrahy, Junfeng Yang, Chad Verbowski, Arunvijay Kumar:
Context-based Online Configuration-Error Detection. USENIX ATC 2011 - 2010
- [j15]Gagan Aggarwal, Rina Panigrahy, Tomás Feder, Dilys Thomas, Krishnaram Kenthapadi, Samir Khuller, An Zhu:
Achieving anonymity via clustering. ACM Trans. Algorithms 6(3): 49:1-49:19 (2010) - [c48]Rina Panigrahy, Kunal Talwar, Udi Wieder:
Lower Bounds on Near Neighbor Search via Metric Expansion. FOCS 2010: 805-814 - [c47]Anish Das Sarma, Atish Das Sarma, Sreenivas Gollapudi, Rina Panigrahy:
Ranking mechanisms in twitter-like forums. WSDM 2010: 21-30 - [c46]Atish Das Sarma, Sreenivas Gollapudi, Marc Najork
A sketch-based distance oracle for web-scale graphs. WSDM 2010: 401-410 - [i14]Sreenivas Gollapudi, Rina Panigrahy:
Revisiting the Examination Hypothesis with Query Specific Position Bias. CoRR abs/1003.2458 (2010) - [i13]Rina Panigrahy, Kunal Talwar, Udi Wieder:
Lower Bounds on Near Neighbor Search via Metric Expansion. CoRR abs/1005.0418 (2010) - [i12]Michael Kapralov, Rina Panigrahy:
Prediction strategies without loss. CoRR abs/1008.3672 (2010) - [i11]Anish Das Sarma, Sreenivas Gollapudi, Rina Panigrahy, Li Zhang:
Understanding Fashion Cycles as a Social Choice. CoRR abs/1009.2617 (2010) - [i10]Rina Panigrahy:
A non-expert view on Turing machines, Proof Verifiers, and Mental reasoning. CoRR abs/1011.0046 (2010) - [i9]Rina Panigrahy:
Understanding the Cycle of Knowledge: Its rise, preservation and decay. CoRR abs/1011.1979 (2010)
2000 – 2009
- 2009
- [j14]Sriram C. Krishnan, Rina Panigrahy, Sunil Parthasarathy:
Error-Correcting Codes for Ternary Content Addressable Memories. IEEE Trans. Computers 58(2): 275-279 (2009) - [j13]Miad Faezipour
A hardware platform for efficient worm outbreak detection. ACM Trans. Design Autom. Electr. Syst. 14(4): 49:1-49:29 (2009) - [c45]Noga Alon, Rina Panigrahy, Sergey Yekhanin:
Deterministic Approximation Algorithms for the Nearest Codeword Problem. APPROX-RANDOM 2009: 339-351 - [c44]Atish Das Sarma, Sreenivas Gollapudi, Rina Panigrahy:
Sparse Cut Projections in Graph Streams. ESA 2009: 480-491 - [c43]Andrew McGregor, Krzysztof Onak, Rina Panigrahy:
The Oil Searching Problem. ESA 2009: 504-515 - [c42]Eric Lehman, Rina Panigrahy:
3.5-Way Cuckoo Hashing for the Price of 2-and-a-Bit. ESA 2009: 671-681 - [c41]Marc Najork
Less is more: sampling the neighborhood graph makes SALSA better and faster. WSDM 2009: 242-251 - [i8]Noga Alon, Rina Panigrahy, Sergey Yekhanin:
Deterministic approximation algorithms for the nearest codeword problem. Algebraic Methods in Computational Complexity 2009 - 2008
- [c40]Rina Panigrahy, Kunal Talwar, Udi Wieder:
A Geometric Approach to Lower Bounds for Approximate Near-Neighbor Search and Partial Match. FOCS 2008: 414-423 - [c39]Rina Panigrahy:
An Improved Algorithm Finding Nearest Neighbor Using Kd-trees. LATIN 2008: 387-398 - [c38]Atish Das Sarma, Sreenivas Gollapudi, Rina Panigrahy:
Estimating PageRank on graph streams. PODS 2008: 69-78 - [c37]Sreenivas Gollapudi, Rina Panigrahy:
The power of two min-hashes for similarity search among hierarchical data objects. PODS 2008: 211-220 - [c36]Yinglian Xie, Fang Yu, Kannan Achan, Rina Panigrahy, Geoff Hulten, Ivan Osipkov:
Spamming botnets: signatures and characteristics. SIGCOMM 2008: 171-182 - [c35]Thomas Holenstein, Michael Mitzenmacher, Rina Panigrahy, Udi Wieder:
Trace reconstruction with constant deletion probability and related results. SODA 2008: 389-398 - [c34]Nitin Agrawal, Vijayan Prabhakaran, Ted Wobber, John D. Davis, Mark S. Manasse, Rina Panigrahy:
Design Tradeoffs for SSD Performance. USENIX ATC 2008: 57-70 - [i7]Alexandr Andoni, Andrew McGregor, Krzysztof Onak, Rina Panigrahy:
Better Bounds for Frequency Moments in Random-Order Streams. CoRR abs/0808.2222 (2008) - [i6]Noga Alon, Rina Panigrahy, Sergey Yekhanin:
Deterministic Approximation Algorithms for the Nearest Codeword Problem. Electron. Colloquium Comput. Complex. TR08 (2008) - 2007
- [b1]Rina Panigrahy:
Hashing, searching, sketching. Stanford University, USA, 2007 - [j12]Tomás Feder, Rajeev Motwani, Liadan O'Callaghan, Chris Olston, Rina Panigrahy:
Computing shortest paths with uncertainty. J. Algorithms 62(1): 1-18 (2007) - [j11]Rajeev Motwani, Assaf Naor, Rina Panigrahy:
Lower Bounds on Locality Sensitive Hashing. SIAM J. Discret. Math. 21(4): 930-935 (2007) - [j10]Renato Carmo, Tomás Feder, Yoshiharu Kohayakawa, Eduardo Sany Laber, Rajeev Motwani, Liadan O'Callaghan, Rina Panigrahy, Dilys Thomas:
Querying priced information in databases: The conjunctive case. ACM Trans. Algorithms 3(1): 9:1-9:22 (2007) - [j9]Mohammad J. Akhbarizadeh, Mehrdad Nourani, Rina Panigrahy, Samar Sharma:
A TCAM-Based Parallel Architecture for High-Speed Packet Forwarding. IEEE Trans. Computers 56(1): 58-72 (2007) - [c33]Ravi Kumar, Rina Panigrahy:
On Finding Frequent Elements in a Data Stream. APPROX-RANDOM 2007: 584-595 - [c32]Rina Panigrahy, Dilys Thomas:
Finding Frequent Elements in Non-bursty Streams. ESA 2007: 53-62 - [c31]Miad Faezipour
A Real-Time Worm Outbreak Detection System Using Shared Counters. Hot Interconnects 2007: 65-72 - [c30]Rajeev Motwani, Rina Panigrahy, Ying Xu:
Estimating Sum by Weighted Sampling. ICALP 2007: 53-64 - [c29]Sreenivas Gollapudi, Marc Najork
Using Bloom Filters to Speed Up HITS-Like Ranking Algorithms. WAW 2007: 195-201 - 2006
- [c28]Rajeev Motwani, Rina Panigrahy, Ying Xu:
Fractional Matching Via Balls-and-Bins. APPROX-RANDOM 2006: 487-498 - [c27]Sreenivas Gollapudi, Rina Panigrahy:
Exploiting asymmetry in hierarchical topic extraction. CIKM 2006: 475-482 - [c26]Andrei Z. Broder, Marcus Fontoura, Vanja Josifovski, Ravi Kumar, Rajeev Motwani, Shubha U. Nabar, Rina Panigrahy, Andrew Tomkins, Ying Xu:
Estimating corpus size via queries. CIKM 2006: 594-603 - [c25]Sreenivas Gollapudi, Rina Panigrahy:
A dictionary for approximate string search and longest prefix search. CIKM 2006: 768-775 - [c24]Rajeev Motwani, Assaf Naor, Rina Panigrahy:
Lower bounds on locality sensitive hashing. SCG 2006: 154-157 - [c23]Flavio Bonomi, Michael Mitzenmacher, Rina Panigrahy, Sushil Singh, George Varghese:
An Improved Construction for Counting Bloom Filters. ESA 2006: 684-695 - [c22]Gagan Aggarwal, Tomás Feder, Krishnaram Kenthapadi, Samir Khuller, Rina Panigrahy, Dilys Thomas, An Zhu:
Achieving anonymity via clustering. PODS 2006: 153-162 - [c21]Flavio Bonomi, Michael Mitzenmacher, Rina Panigrahy, Sushil Singh, George Varghese:
Beyond bloom filters: from approximate membership checks to approximate state machines. SIGCOMM 2006: 315-326 - [c20]Krishnaram Kenthapadi, Rina Panigrahy:
Balanced allocation on graphs. SODA 2006: 434-443 - [c19]David Arthur, Rina Panigrahy:
Analyzing BitTorrent and related peer-to-peer networks. SODA 2006: 961-969 - [c18]Rina Panigrahy:
Entropy based nearest neighbor search in high dimensions. SODA 2006: 1186-1195 - 2005
- [j8]Moses Charikar
The smallest grammar problem. IEEE Trans. Inf. Theory 51(7): 2554-2576 (2005) - [c17]Mohammad J. Akhbarizadeh, Mehrdad Nourani, Rina Panigrahy, Samar Sharma:
High-Speed and Low-Power Network Search Engine Using Adaptive Block-Selection Scheme. Hot Interconnects 2005: 73-78 - [c16]Gagan Aggarwal, Tomás Feder, Rajeev Motwani, Rina Panigrahy, An Zhu:
Algorithms for the Database Layout Problem. ICDT 2005: 189-203 - [c15]Gagan Aggarwal, Tomás Feder, Krishnaram Kenthapadi, Rajeev Motwani, Rina Panigrahy, Dilys Thomas, An Zhu:
Anonymizing Tables. ICDT 2005: 246-258 - [c14]Rina Panigrahy:
Efficient hashing with lookups in two memory accesses. SODA 2005: 830-839 - [i5]Rina Panigrahy:
Entropy based Nearest Neighbor Search in High Dimensions. CoRR abs/cs/0510019 (2005) - [i4]Krishnaram Kenthapadi, Rina Panigrahy:
Balanced Allocation on Graphs. CoRR abs/cs/0510086 (2005) - [i3]Rajeev Motwani, Assaf Naor, Rina Panigrahy:
Lower bounds on Locality Sensitive Hashing. CoRR abs/cs/0510088 (2005) - 2004
- [j7]Moses Charikar
Clustering to minimize the sum of cluster diameters. J. Comput. Syst. Sci. 68(2): 417-441 (2004) - [j6]Tomás Feder, Rajeev Motwani, Rina Panigrahy, Steven S. Seiden, Rob van Stee, An Zhu:
Combining request scheduling with web caching. Theor. Comput. Sci. 324(2-3): 201-218 (2004) - [c13]Punit Bhargava, Sriram C. Krishnan, Rina Panigrahy:
Efficient multicast on a terabit router. Hot Interconnects 2004: 61-67 - [i2]Rina Panigrahy:
Minimum Enclosing Polytope in High Dimensions. CoRR cs.CG/0407020 (2004) - [i1]Rina Panigrahy:
Efficient Hashing with Lookups in two Memory Accesses. CoRR cs.DS/0407023 (2004) - 2003
- [j5]Mayur Datar, Tomás Feder, Aristides Gionis, Rajeev Motwani, Rina Panigrahy:
A combinatorial algorithm for MAX CSP. Inf. Process. Lett. 85(6): 307-315 (2003) - [j4]Rina Panigrahy, Samar Sharma:
Sorting and Searching using Ternary CAMs. IEEE Micro 23(1): 44-53 (2003) - [j3]Tomás Feder, Rajeev Motwani, Rina Panigrahy, Chris Olston, Jennifer Widom:
Computing the Median with Uncertainty. SIAM J. Comput. 32(2): 538-547 (2003) - [c12]Tomás Feder, Adam Meyerson, Rajeev Motwani, Liadan O'Callaghan, Rina Panigrahy:
Representing Graph Metrics with Fewest Edges. STACS 2003: 355-366 - [c11]Tomás Feder, Rajeev Motwani, Liadan O'Callaghan, Chris Olston, Rina Panigrahy:
Computing Shortest Paths with Uncertainty. STACS 2003: 367-378 - [c10]Moses Charikar
Better streaming algorithms for clustering problems. STOC 2003: 30-39 - 2002
- [c9]Samar Sharma, Rina Panigrahy:
Sorting and Searching Using Ternary CAMs. Hot Interconnects 2002: 101-106 - [c8]Rina Panigrahy, Samar Sharma:
Reducing TCAM Power Consumption and Increasing Throughput. Hot Interconnects 2002: 107-114 - [c7]Moses Charikar
New Algorithms for Subset Query, Partial Match, Orthogonal Range Searching, and Related Problems. ICALP 2002: 451-462 - [c6]Tomás Feder, Rajeev Motwani, Rina Panigrahy, An Zhu:
Web caching with request reordering. SODA 2002: 104-105 - [c5]Moses Charikar
Approximating the smallest grammar: Kolmogorov complexity in natural models. STOC 2002: 792-801 - 2001
- [c4]Moses Charikar
Clustering to minimize the sum of cluster diameters. STOC 2001: 1-10 - 2000
- [c3]Rajeev Motwani, Rina Panigrahy, Vijay A. Saraswat, Suresh Venkatasubramanian:
On the decidability of accessibility problems (extended abstract). STOC 2000: 306-315 - [c2]Tomás Feder, Rajeev Motwani, Rina Panigrahy, Chris Olston, Jennifer Widom:
Computing the median with uncertainty. STOC 2000: 602-607
1990 – 1999
- 1998
- [j2]Rina Panigrahy, Sundar Vishwanathan:
An O(log* n) Approximation Algorithm for the Asymmetric p-Center Problem. J. Algorithms 27(2): 259-268 (1998) - 1997
- [j1]Ravi Kumar, Rina Panigrahy, Alexander Russell
A Note on Optical Routing on Trees. Inf. Process. Lett. 62(6): 295-300 (1997) - [c1]David R. Karger, Eric Lehman, Frank Thomson Leighton, Rina Panigrahy, Matthew S. Levine, Daniel Lewin:
Consistent Hashing and Random Trees: Distributed Caching Protocols for Relieving Hot Spots on the World Wide Web. STOC 1997: 654-663
Coauthor Index
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