Dharmendra S. Modha

84 papers A* 6A 9B 12C 2Journal 36Unranked 19
YearRankTypeTitle / Venue / Authors
2025 J jnl
A Scalable NorthPole System with End-to-End Vertical Integration for Low-Latency and Energy-Efficient LLM Inference.
CoRR
Michael V. DeBole, Rathinakumar Appuswamy, Neil McGlohon, Brian Taba, Steven K. Esser, Filipp Akopyan, John V. Arthur, Arnon Amir, Alexander Andreopoulos, Peter J. Carlson, Andrew S. Cassidy, Pallab Datta, Myron D. Flickner, Rajamohan Gandhasri, Guillaume J. Garreau, Megumi Ito, Jennifer L. Klamo, Jeffrey A. Kusnitz, Nathaniel J. McClatchey, Jeffrey L. McKinstry, Tapan K. Nayak, Carlos Ortega Otero, Hartmut Penner, William P. Risk, Jun Sawada, Jay Sivagnaname, Daniel F. Smith, Rafael Sousa, Ignacio Terrizzano, Takanori Ueda, Trent Gray-Donald, David D. Cox, Dharmendra S. Modha
2025 J jnl
Mitigating hallucinations and omissions in LLMs for invertible problems: An application to hardware logic design automation.
CoRR
Andrew S. Cassidy, Guillaume Garreau, Jay Sivagnaname, Mike Grassi, Bernard Brezzo, John V. Arthur, Dharmendra S. Modha
2025 — conf
SiLQ: Simple Large Language Model Quantization-Aware Training.
IJCNLP-AACL (Findings)
Steven K. Esser, Jeffrey L. McKinstry, Deepika Bablani, Rathinakumar Appuswamy, Dharmendra S. Modha
2025 J jnl
SiLQ: Simple Large Language Model Quantization-Aware Training.
CoRR
Steven K. Esser, Jeffrey L. McKinstry, Deepika Bablani, Rathinakumar Appuswamy, Dharmendra S. Modha
2025 — conf
The NorthPole Validator: A Cycle-Accurate Simulator for HW/SW Codesign of a Prescheduled Neural Inference Accelerator.
HPEC
Alexander Andreopoulos, Michael V. DeBole, Jeffrey A. Kusnitz, Nathaniel J. McClatchey, Tapan K. Nayak, Daniel F. Smith, Brian Taba, Filipp Akopyan, Rathinakumar Appuswamy, John V. Arthur, Andrew S. Cassidy, Pallab Datta, Carlos Ortega Otero, William P. Risk, Jun Sawada, Myron D. Flickner, Dharmendra S. Modha
2024 — conf
11.4 IBM NorthPole: An Architecture for Neural Network Inference with a 12nm Chip.
ISSCC
Andrew S. Cassidy, John V. Arthur, Filipp Akopyan, Alexander Andreopoulos, Rathinakumar Appuswamy, Pallab Datta, Michael V. DeBole, Steven K. Esser, Carlos Ortega Otero, Jun Sawada, Brian Taba, Arnon Amir, Deepika Bablani, Peter J. Carlson, Myron D. Flickner, Rajamohan Gandhasri, Guillaume Garreau, Megumi Ito, Jennifer L. Klamo, Jeffrey A. Kusnitz, Nathaniel J. McClatchey, Jeffrey L. McKinstry, Yutaka Y. Nakamura, Tapan K. Nayak, William P. Risk, Kai Schleupen, Ben Shaw, Jay Sivagnaname, Daniel F. Smith, Ignacio Terrizzano, Takanori Ueda, Dharmendra S. Modha
2024 — conf
Breakthrough Edge AI Inference Performance Using Northpole in 3U Vpx Form Factor.
HPEC
Filipp Akopyan, William P. Risk, John V. Arthur, Andrew S. Cassidy, Michael V. DeBole, Carlos Ortega Otero, Jun Sawada, Evan Colgan, Michael E. Criscolo, Phillip V. Mann, Heinz Baier, Kai Schleupen, Arnon Amir, Alexander Andreopoulos, Rathinakumar Appuswamy, Deepika Bablani, Peter J. Carlson, Pallab Datta, Steven K. Esser, Myron D. Flickner, Rajamohan Gandhasri, Guillaume J. Garreau, Megumi Ito, Jennifer L. Klamo, Jeffrey A. Kusnitz, Nathaniel J. McClatchey, Neil McGlohon, Jeffrey L. McKinstry, Yutaka Y. Nakamura, Tapan K. Nayak, Jay Sivagnaname, Daniel F. Smith, Rafael Sousa, Brian Taba, Ignacio Terrizzano, Takanori Ueda, Dharmendra S. Modha
2024 — conf
Breakthrough Low-Latency, High-Energy-Efficiency LLM Inference Performance Using NorthPole.
HPEC
Rathinakumar Appuswamy, Michael V. DeBole, Brian Taba, Steven K. Esser, Andrew S. Cassidy, Arnon Amir, Alexander Andreopoulos, Deepika Bablani, Pallab Datta, Jeffrey A. Kusnitz, Nathaniel J. McClatchey, Neil McGlohon, Jeffrey L. McKinstry, Tapan K. Nayak, Daniel F. Smith, Rafael Sousa, Ignacio Terrizzano, Filipp Akopyan, Peter J. Carlson, Rajamohan Gandhasri, Guillaume Garreau, Nelson M. Gonzalez, Megumi Ito, Jennifer L. Klamo, Yutaka Y. Nakamura, Carlos Ortega Otero, William P. Risk, Jun Sawada, Kai Schleupen, Jay Sivagnaname, Matthew Stallone, Takanori Ueda, Myron D. Flickner, John V. Arthur, Rameswar Panda, David D. Cox, Dharmendra S. Modha
2023 J jnl
Efficient and Effective Methods for Mixed Precision Neural Network Quantization for Faster, Energy-efficient Inference.
CoRR
Deepika Bablani, Jeffrey L. McKinstry, Steven K. Esser, Rathinakumar Appuswamy, Dharmendra S. Modha
2023 — conf
IBM NorthPole Neural Inference Machine.
HCS
Dharmendra S. Modha, Filipp Akopyan, Alexander Andreopoulos, Rathinakumar Appuswamy, John V. Arthur, Andrew S. Cassidy, Pallab Datta, Michael V. DeBole, Steven K. Esser, Carlos Ortega Otero, Jun Sawada, Brian Taba, Arnon Amir, Deepika Bablani, Peter J. Carlson, Myron D. Flickner, Rajamohan Gandhasri, Guillaume Garreau, Megumi Ito, Jennifer L. Klamo, Jeffrey A. Kusnitz, Nathaniel J. McClatchey, Jeffrey L. McKinstry, Yutaka Y. Nakamura, Tapan K. Nayak, William P. Risk, Kai Schleupen, Ben Shaw, Jay Sivagnaname, Daniel F. Smith, Ignacio Terrizzano, Takanori Ueda
2020 A* conf
Learned Step Size quantization.
ICLR
Steven K. Esser, Jeffrey L. McKinstry, Deepika Bablani, Rathinakumar Appuswamy, Dharmendra S. Modha
2019 — conf
Discovering Low-Precision Networks Close to Full-Precision Networks for Efficient Inference.
EMC2@NeurIPS
Jeffrey L. McKinstry, Steven K. Esser, Rathinakumar Appuswamy, Deepika Bablani, John V. Arthur, Izzet B. Yildiz, Dharmendra S. Modha
2019 J jnl
Learned Step Size Quantization.
CoRR
Steven K. Esser, Jeffrey L. McKinstry, Deepika Bablani, Rathinakumar Appuswamy, Dharmendra S. Modha
2019 J jnl
TrueNorth: Accelerating From Zero to 64 Million Neurons in 10 Years.
Computer
Michael V. DeBole, Brian Taba, Arnon Amir, Filipp Akopyan, Alexander Andreopoulos, William P. Risk, Jeff Kusnitz, Carlos Ortega Otero, Tapan K. Nayak, Rathinakumar Appuswamy, Peter J. Carlson, Andrew S. Cassidy, Pallab Datta, Steven K. Esser, Guillaume Garreau, Kevin L. Holland, Scott Lekuch, Michael Mastro, Jeffrey L. McKinstry, Carmelo di Nolfo, Brent Paulovicks, Jun Sawada, Kai Schleupen, Benjamin G. Shaw, Jennifer L. Klamo, Myron D. Flickner, John V. Arthur, Dharmendra S. Modha
2018 J jnl
Discovering Low-Precision Networks Close to Full-Precision Networks for Efficient Embedded Inference.
CoRR
Jeffrey L. McKinstry, Steven K. Esser, Rathinakumar Appuswamy, Deepika Bablani, John V. Arthur, Izzet B. Yildiz, Dharmendra S. Modha
2018 J jnl
Low Precision Policy Distillation with Application to Low-Power, Real-time Sensation-Cognition-Action Loop with Neuromorphic Computing.
CoRR
Jeffrey L. McKinstry, Davis R. Barch, Deepika Bablani, Michael DeBole, Steven K. Esser, Jeffrey A. Kusnitz, John V. Arthur, Dharmendra S. Modha
2017 A* conf
A Low Power, Fully Event-Based Gesture Recognition System.
CVPR
Arnon Amir, Brian Taba, David J. Berg, Timothy Melano, Jeffrey L. McKinstry, Carmelo di Nolfo, Tapan K. Nayak, Alexander Andreopoulos, Guillaume Garreau, Marcela Mendoza, Jeff Kusnitz, Michael DeBole, Steven K. Esser, Tobi Delbruck, Myron Flickner, Dharmendra S. Modha
2017 J jnl
Always-On Speech Recognition Using TrueNorth, a Reconfigurable, Neurosynaptic Processor.
IEEE Trans. Computers
Wei-Yu Tsai, Davis R. Barch, Andrew S. Cassidy, Michael V. DeBole, Alexander Andreopoulos, Bryan L. Jackson, Myron D. Flickner, John V. Arthur, Dharmendra S. Modha, John Sampson, Vijaykrishnan Narayanan
2016 J jnl
Convolutional Networks for Fast, Energy-Efficient Neuromorphic Computing.
CoRR
Steven K. Esser, Paul A. Merolla, John V. Arthur, Andrew S. Cassidy, Rathinakumar Appuswamy, Alexander Andreopoulos, David J. Berg, Jeffrey L. McKinstry, Timothy Melano, Davis R. Barch, Carmelo di Nolfo, Pallab Datta, Arnon Amir, Brian Taba, Myron D. Flickner, Dharmendra S. Modha
2016 J jnl
Convolutional networks for fast, energy-efficient neuromorphic computing.
Proc. Natl. Acad. Sci. USA
Steven K. Esser, Paul A. Merolla, John V. Arthur, Andrew S. Cassidy, Rathinakumar Appuswamy, Alexander Andreopoulos, David J. Berg, Jeffrey L. McKinstry, Timothy Melano, Davis R. Barch, Carmelo di Nolfo, Pallab Datta, Arnon Amir, Brian Taba, Myron D. Flickner, Dharmendra S. Modha
2016 J jnl
Deep neural networks are robust to weight binarization and other non-linear distortions.
CoRR
Paul Merolla, Rathinakumar Appuswamy, John V. Arthur, Steven K. Esser, Dharmendra S. Modha
2016 B conf
LATTE: Low-power Audio Transform with TrueNorth Ecosystem.
IJCNN
Wei-Yu Tsai, Davis R. Barch, Andrew S. Cassidy, Michael V. DeBole, Alexander Andreopoulos, Bryan L. Jackson, Myron D. Flickner, Dharmendra S. Modha, Jack Sampson, Vijaykrishnan Narayanan
2016 J jnl
Mapping Generative Models onto a Network of Digital Spiking Neurons.
IEEE Trans. Biomed. Circuits Syst.
Bruno U. Pedroni, Srinjoy Das, John V. Arthur, Paul A. Merolla, Bryan L. Jackson, Dharmendra S. Modha, Kenneth Kreutz-Delgado, Gert Cauwenberghs
2016 C conf
Real-time sensory information processing using the TrueNorth Neurosynaptic System.
ISCAS
Andreas G. Andreou, Andrew A. Dykman, Kate D. Fischl, Guillaume Garreau, Daniel R. Mendat, Garrick Orchard, Andrew S. Cassidy, Paul Merolla, John V. Arthur, Rodrigo Alvarez-Icaza, Bryan L. Jackson, Dharmendra S. Modha
2016 J jnl
Structured Convolution Matrices for Energy-efficient Deep learning.
CoRR
Rathinakumar Appuswamy, Tapan K. Nayak, John V. Arthur, Steven K. Esser, Paul Merolla, Jeffrey L. McKinstry, Timothy Melano, Myron Flickner, Dharmendra S. Modha
2016 A conf
Truenorth ecosystem for brain-inspired computing: scalable systems, software, and applications.
SC
Jun Sawada, Filipp Akopyan, Andrew S. Cassidy, Brian Taba, Michael V. DeBole, Pallab Datta, Rodrigo Alvarez-Icaza, Arnon Amir, John V. Arthur, Alexander Andreopoulos, Rathinakumar Appuswamy, Heinz Baier, Davis Barch, David J. Berg, Carmelo di Nolfo, Steven K. Esser, Myron Flickner, Thomas A. Horvath, Bryan L. Jackson, Jeff Kusnitz, Scott Lekuch, Michael Mastro, Timothy Melano, Paul A. Merolla, Steven E. Millman, Tapan K. Nayak, Norm Pass, Hartmut E. Penner, William P. Risk, Kai Schleupen, Benjamin G. Shaw, Hayley Wu, Brian Giera, Adam T. Moody, T. Nathan Mundhenk, Brian Van Essen, Eric X. Wang, David P. Widemann, Qing Wu, William E. Murphy, Jamie K. Infantolino, James A. Ross, Dale R. Shires, Manuel M. Vindiola, Raju Namburu, Dharmendra S. Modha
2015 — conf
Backpropagation for Energy-Efficient Neuromorphic Computing.
NIPS
Steven K. Esser, Rathinakumar Appuswamy, Paul Merolla, John V. Arthur, Dharmendra S. Modha
2015 B conf
Brain-Inspired Computing.
PACT
Dharmendra S. Modha
2015 J jnl
Gibbs Sampling with Low-Power Spiking Digital Neurons.
CoRR
Srinjoy Das, Bruno U. Pedroni, Paul Merolla, John V. Arthur, Andrew S. Cassidy, Bryan L. Jackson, Dharmendra S. Modha, Gert Cauwenberghs, Kenneth Kreutz-Delgado
2015 C conf
Gibbs sampling with low-power spiking digital neurons.
ISCAS
Srinjoy Das, Bruno Umbria Pedroni, Paul Merolla, John V. Arthur, Andrew S. Cassidy, Bryan L. Jackson, Dharmendra S. Modha, Gert Cauwenberghs, Kenneth Kreutz-Delgado
2015 J jnl
Mapping Generative Models onto Networks of Digital Spiking Neurons.
CoRR
Bruno U. Pedroni, Srinjoy Das, John V. Arthur, Paul Merolla, Bryan L. Jackson, Dharmendra S. Modha, Kenneth Kreutz-Delgado, Gert Cauwenberghs
2015 J jnl
TrueNorth: Design and Tool Flow of a 65 mW 1 Million Neuron Programmable Neurosynaptic Chip.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.
Filipp Akopyan, Jun Sawada, Andrew Cassidy, Rodrigo Alvarez-Icaza, John V. Arthur, Paul Merolla, Nabil Imam, Yutaka Y. Nakamura, Pallab Datta, Gi-Joon Nam, Brian Taba, Michael P. Beakes, Bernard Brezzo, Jente B. Kuang, Rajit Manohar, William P. Risk, Bryan L. Jackson, Dharmendra S. Modha
2015 J jnl
Visual saliency on networks of neurosynaptic cores.
IBM J. Res. Dev.
Alexander Andreopoulos, Brian Taba, Andrew S. Cassidy, Rodrigo Alvarez-Icaza, Myron Flickner, William P. Risk, Arnon Amir, Paul Merolla, John V. Arthur, David J. Berg, Jeffrey A. Kusnitz, Pallab Datta, Steven K. Esser, Rathinakumar Appuswamy, Davis Barch, Dharmendra S. Modha
2014 A conf
Real-Time Scalable Cortical Computing at 46 Giga-Synaptic OPS/Watt with ~100× Speedup in Time-to-Solution and ~100, 000× Reduction in Energy-to-Solution.
SC
Andrew S. Cassidy, Rodrigo Alvarez-Icaza, Filipp Akopyan, Jun Sawada, John V. Arthur, Paul Merolla, Pallab Datta, Marc González Tallada, Brian Taba, Alexander Andreopoulos, Arnon Amir, Steven K. Esser, Jeff Kusnitz, Rathinakumar Appuswamy, Chuck Haymes, Bernard Brezzo, Roger Moussalli, Ralph Bellofatto, Christian W. Baks, Michael Mastro, Kai Schleupen, Charles E. Cox, Ken Inoue, Steven E. Millman, Nabil Imam, Emmett McQuinn, Yutaka Y. Nakamura, Ivan Vo, Chen Guok, Don Nguyen, Scott Lekuch, Sameh W. Asaad, Daniel J. Friedman, Bryan L. Jackson, Myron Flickner, William P. Risk, Rajit Manohar, Dharmendra S. Modha
2013 B conf
Cognitive computing building block: A versatile and efficient digital neuron model for neurosynaptic cores.
IJCNN
Andrew S. Cassidy, Paul Merolla, John V. Arthur, Steven K. Esser, Bryan L. Jackson, Rodrigo Alvarez-Icaza, Pallab Datta, Jun Sawada, Theodore M. Wong, Vitaly Feldman, Arnon Amir, Daniel Ben Dayan Rubin, Filipp Akopyan, Emmett McQuinn, William P. Risk, Dharmendra S. Modha
2013 B conf
Cognitive computing programming paradigm: A Corelet Language for composing networks of neurosynaptic cores.
IJCNN
Arnon Amir, Pallab Datta, William P. Risk, Andrew S. Cassidy, Jeffrey A. Kusnitz, Steven K. Esser, Alexander Andreopoulos, Theodore M. Wong, Myron Flickner, Rodrigo Alvarez-Icaza, Emmett McQuinn, Ben Shaw, Norm Pass, Dharmendra S. Modha
2013 B conf
Cognitive computing systems: Algorithms and applications for networks of neurosynaptic cores.
IJCNN
Steven K. Esser, Alexander Andreopoulos, Rathinakumar Appuswamy, Pallab Datta, Davis Barch, Arnon Amir, John V. Arthur, Andrew Cassidy, Myron Flickner, Paul Merolla, Shyamal Chandra, Nicola Basilico, Stefano Carpin, Tom Zimmerman, Frank Zee, Rodrigo Alvarez-Icaza, Jeffrey A. Kusnitz, Theodore M. Wong, William P. Risk, Emmett McQuinn, Tapan K. Nayak, Raghavendra Singh, Dharmendra S. Modha
2013 J jnl
Nanoscale electronic synapses using phase change devices.
ACM J. Emerg. Technol. Comput. Syst.
Bryan L. Jackson, Bipin Rajendran, Gregory S. Corrado, Matthew J. Breitwisch, Geoffrey W. Burr, Roger Cheek, Kailash Gopalakrishnan, Simone Raoux, Charles T. Rettner, Alvaro Padilla, Alejandro G. Schrott, Rohit S. Shenoy, Bülent N. Kurdi, Chung Hon Lam, Dharmendra S. Modha
2013 — conf
SyNAPSE: Jun Sawada.
ACSD
Jun Sawada, Dharmendra S. Modha
2012 — conf
A Digital Neurosynaptic Core Using Event-Driven QDI Circuits.
ASYNC
Nabil Imam, Filipp Akopyan, John V. Arthur, Paul Merolla, Rajit Manohar, Dharmendra S. Modha
2012 B conf
Building block of a programmable neuromorphic substrate: A digital neurosynaptic core.
IJCNN
John V. Arthur, Paul Merolla, Filipp Akopyan, Rodrigo Alvarez-Icaza, Andrew Cassidy, Shyamal Chandra, Steven K. Esser, Nabil Imam, William P. Risk, Daniel Ben Dayan Rubin, Rajit Manohar, Dharmendra S. Modha
2012 A conf
Compass: a scalable simulator for an architecture for cognitive computing.
SC
Robert Preissl, Theodore M. Wong, Pallab Datta, Myron Flickner, Raghavendra Singh, Steven K. Esser, William P. Risk, Horst D. Simon, Dharmendra S. Modha
2012 J jnl
Optimal Lempel-Ziv based lossy compression for memoryless data: how to make the right mistakes
CoRR
Narayana P. Santhanam, Dharmendra S. Modha
2011 — conf
A 45nm CMOS neuromorphic chip with a scalable architecture for learning in networks of spiking neurons.
CICC
Jae-sun Seo, Bernard Brezzo, Yong Liu, Benjamin D. Parker, Steven K. Esser, Robert K. Montoye, Bipin Rajendran, José A. Tierno, Leland Chang, Dharmendra S. Modha, Daniel J. Friedman
2011 — conf
A digital neurosynaptic core using embedded crossbar memory with 45pJ per spike in 45nm.
CICC
Paul Merolla, John V. Arthur, Filipp Akopyan, Nabil Imam, Rajit Manohar, Dharmendra S. Modha
2011 J jnl
Cognitive computing.
Commun. ACM
Dharmendra S. Modha, Rajagopal Ananthanarayanan, Steven K. Esser, Anthony Ndirango, Anthony J. Sherbondy, Raghavendra Singh
2011 — conf
Lossy Lempel-Ziv like compression algorithms for memoryless sources.
Allerton
Narayana Prasad Santhanam, Dharmendra S. Modha
2010 B conf
Binding sparse spatiotemporal patterns in spiking computation.
IJCNN
Steven K. Esser, Anthony Ndirango, Dharmendra S. Modha
2009 A conf
The cat is out of the bag: cortical simulations with 10
SC
Rajagopal Ananthanarayanan, Steven K. Esser, Horst D. Simon, Dharmendra S. Modha
2009 — conf
Think Global, Act Local; Projectome Estimation with BlueMatter.
MICCAI (1)
Anthony J. Sherbondy, Robert F. Dougherty, Rajagopal Ananthanarayanan, Dharmendra S. Modha, Brian A. Wandell
2007 J jnl
A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation.
J. Mach. Learn. Res.
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu, Dharmendra S. Modha
2007 A conf
Anatomy of a cortical simulator.
SC
Rajagopal Ananthanarayanan, Dharmendra S. Modha
2006 — conf
Adaptive Website Design Using Caching Algorithms.
WebKDD
Justin Brickell, Inderjit S. Dhillon, Dharmendra S. Modha
2006 B conf
Making the Correct Mistakes.
DCC
Dharmendra S. Modha, Narayana P. Santhanam
2005 — conf
SARC: Sequential Prefetching in Adaptive Replacement Cache.
USENIX ATC, General Track
Binny S. Gill, Dharmendra S. Modha
2005 A conf
WOW: Wise Ordering for Writes - Combining Spatial and Temporal Locality in Non-Volatile Caches.
FAST
Binny S. Gill, Dharmendra S. Modha
2004 A* conf
A generalized maximum entropy approach to bregman co-clustering and matrix approximation.
KDD
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu, Dharmendra S. Modha
2004 A conf
CAR: Clock with Adaptive Replacement.
FAST
Sorav Bansal, Dharmendra S. Modha
2004 B conf
Finite-state rate-distortion for individual sequences.
ISIT
Dharmendra S. Modha, Daniela Pucci de Farias
2004 A* conf
Fully automatic cross-associations.
KDD
Deepayan Chakrabarti, Spiros Papadimitriou, Dharmendra S. Modha, Christos Faloutsos
2004 J jnl
Outperforming LRU with an Adaptive Replacement Cache Algorithm.
Computer
Nimrod Megiddo, Dharmendra S. Modha
2003 A conf
ARC: A Self-Tuning, Low Overhead Replacement Cache.
FAST
Nimrod Megiddo, Dharmendra S. Modha
2003 B conf
CacheCOW: QoS for Storage System Caches.
IWQoS
Pawan Goyal, Divyesh Jadav, Dharmendra S. Modha, Renu Tewari
2003 A* conf
CacheCOW: providing QoS for storage system caches.
SIGMETRICS
Pawan Goyal, Dharmendra S. Modha, Renu Tewari
2003 B conf
Codelet Parsing: Quadratic-time, Sequential, Adaptive Algorithms for Lossy Compression.
DCC
Dharmendra S. Modha
2003 J jnl
Feature Weighting in
Mach. Learn.
Dharmendra S. Modha, W. Scott Spangler
2003 A* conf
Information-theoretic co-clustering.
KDD
Inderjit S. Dhillon, Subramanyam Mallela, Dharmendra S. Modha
2003 J jnl
One Up on LRU.
login Usenix Mag.
Nimrod Megiddo, Dharmendra S. Modha
2002 J jnl
Class visualization of high-dimensional data with applications.
Comput. Stat. Data Anal.
Inderjit S. Dhillon, Dharmendra S. Modha, W. Scott Spangler
2002 J jnl
Links between complexity theory and constrained block coding.
IEEE Trans. Inf. Theory
Larry J. Stockmeyer, Dharmendra S. Modha
2001 J jnl
Art of constructing low-complexity encoders/decoders for constrained block codes.
IEEE J. Sel. Areas Commun.
Dharmendra S. Modha, Brian H. Marcus
2001 J jnl
Concept Decompositions for Large Sparse Text Data Using Clustering.
Mach. Learn.
Inderjit S. Dhillon, Dharmendra S. Modha
2001 — conf
Designing LDPC codes using bit-filling.
ICC
Jorge Campello, Dharmendra S. Modha, Sridhar Rajagopalan
2001 B conf
Extended bit-filling and LDPC code design.
GLOBECOM
Jorge Campello, Dharmendra S. Modha
2001 A conf
Links Between Complexity Theory and Constrained Block Coding.
CCC
Larry J. Stockmeyer, Dharmendra S. Modha
2001 J jnl
Maximum transition run codes for generalized partial response channels.
IEEE J. Sel. Areas Commun.
Roy D. Cideciyan, Evangelos Eleftheriou, Brian H. Marcus, Dharmendra S. Modha
2000 — conf
Clustering hypertext with applications to web searching.
Hypertext
Dharmendra S. Modha, W. Scott Spangler
2000 J jnl
Reversible arithmetic coding for quantum data compression.
IEEE Trans. Inf. Theory
Isaac L. Chuang, Dharmendra S. Modha
1999 — conf
A Data-Clustering Algorithm on Distributed Memory Multiprocessors.
Large-Scale Parallel Data Mining
Inderjit S. Dhillon, Dharmendra S. Modha
1998 J jnl
Memory-Universal Prediction of Stationary Random Processes.
IEEE Trans. Inf. Theory
Dharmendra S. Modha, Elias Masry
1998 J jnl
Prequential and Cross-Validated Regression Estimation.
Mach. Learn.
Dharmendra S. Modha, Elias Masry
1996 J jnl
Minimum complexity regression estimation with weakly dependent observations.
IEEE Trans. Inf. Theory
Dharmendra S. Modha, Elias Masry
1996 J jnl
Rate of Convergence in Density Estimation Using Neural Networks.
Neural Comput.
Dharmendra S. Modha, Elias Masry
1994 J jnl
A learning law for density estimation.
IEEE Trans. Neural Networks
Dharmendra S. Modha, Yeshaiahu Fainman