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ORCIDJanardhan Rao Doppa
Janardhan Rao (Jana) Doppa – Jana Doppa
Person information
- affiliation: Washington State University, Pullman, WA, USA
- affiliation: Oregon State University, Corvallis, OR, USA
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2020 – today
- 2025
[j52]Dina Hussein
, Taha Belkhouja, Ganapati Bhat, Jana Doppa:
Sensor-Aware Data Imputation for Time-Series Machine Learning on Low-Power Wearable Devices. ACM Trans. Design Autom. Electr. Syst. 30(1): 1-27 (2025)- 2024
- [j51]Alan Fern, Margaret Burnett, Joseph R. Davidson, Janardhan Rao Doppa, Paola Pesántez-Cabrera, Ananth Kalyanaraman:
AgAID Institute - AI for agricultural labor and decision support. AI Mag. 45(1): 99-104 (2024) - [j50]Shubhomoy Das, Md. Rakibul Islam, Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa:
Effectiveness of Tree-based Ensembles for Anomaly Discovery: Insights, Batch and Streaming Active Learning. J. Artif. Intell. Res. 80: 127-170 (2024) - [j49]Ching-Yuan Chen, Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty:
Mitigating Slow-to-Write Errors in Memristor-Mapped Graph Neural Networks Induced by Adversarial Attacks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 43(8): 2411-2425 (2024) - [j48]Chukwufumnanya Ogbogu, Gaurav Narang, Biresh Kumar Joardar, Janardhan Rao Doppa, Krishnendu Chakrabarty, Partha Pratim Pande:
HuNT: Exploiting Heterogeneous PIM Devices to Design a 3-D Manycore Architecture for DNN Training. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 43(11): 3300-3311 (2024) - [j47]Xueying Wu, Edward Hanson, Nansu Wang, Qilin Zheng, Xiaoxuan Yang, Huanrui Yang, Shiyu Li, Feng Cheng, Partha Pratim Pande, Janardhan Rao Doppa, Krishnendu Chakrabarty, Hai Li:
Block-Wise Mixed-Precision Quantization: Enabling High Efficiency for Practical ReRAM-Based DNN Accelerators. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 43(12): 4558-4571 (2024) - [j46]Gaurav Narang, Chukwufumnanya Ogbogu, Janardhan Rao Doppa, Partha Pratim Pande:
TEFLON: Thermally Efficient Dataflow-aware 3D NoC for Accelerating CNN Inferencing on Manycore PIM Architectures. ACM Trans. Embed. Comput. Syst. 23(5): 78:1-78:23 (2024) - [j45]Taha Belkhouja, Yan Yan, Janardhan Rao Doppa:
Out-of-distribution Detection in Time-series Domain: A Novel Seasonal Ratio Scoring Approach. ACM Trans. Intell. Syst. Technol. 15(1): 8:1-8:24 (2024) - [j44]Chukwufumnanya Ogbogu, Biresh Kumar Joardar, Krishnendu Chakrabarty, Jana Doppa, Partha Pratim Pande:
Data Pruning-enabled High Performance and Reliable Graph Neural Network Training on ReRAM-based Processing-in-Memory Accelerators. ACM Trans. Design Autom. Electr. Syst. 29(5): 1-29 (2024) - [c89]Alaleh Ahmadianshalchi, Syrine Belakaria, Janardhan Rao Doppa:
Pareto Front-Diverse Batch Multi-Objective Bayesian Optimization. AAAI 2024: 10784-10794 - [c88]Yassine Chemingui, Aryan Deshwal, Trong Nghia Hoang, Janardhan Rao Doppa:
Offline Model-Based Optimization via Policy-Guided Gradient Search. AAAI 2024: 11230-11239 - [c87]Alaleh Ahmadianshalchi, Syrine Belakaria, Janardhan Rao Doppa:
Preference-Aware Constrained Multi-Objective Bayesian Optimization (Student Abstract). AAAI 2024: 23436-23438 - [c86]Alaleh Ahmadianshalchi, Syrine Belakaria, Janardhan Rao Doppa:
Preference-Aware Constrained Multi-Objective Bayesian Optimization. COMAD/CODS 2024: 182-191 - [c85]Pratyush Dhingra, Chukwufumnanya Ogbogu, Biresh Kumar Joardar, Janardhan Rao Doppa, Ananth Kalyanaraman, Partha Pratim Pande:
FARe: Fault-Aware GNN Training on ReRAM-Based PIM Accelerators. DATE 2024: 1-6 - [c84]Harsh Sharma, Gaurav Narang, Janardhan Rao Doppa, Ümit Y. Ogras, Partha Pratim Pande:
Dataflow-Aware PIM-Enabled Manycore Architecture for Deep Learning Workloads. DATE 2024: 1-6 - [c83]Minh Hoang, Azza Fadhel, Aryan Deshwal, Jana Doppa, Trong Nghia Hoang:
Learning Surrogates for Offline Black-Box Optimization via Gradient Matching. ICML 2024 - [c82]Mohammed Amine Gharsallaoui, Bhupinderjeet Singh, Supriya Savalkar, Aryan Deshwal, Ananth Kalyanaraman, Kirti Rajagopalan, Janardhan Rao Doppa:
Streamflow Prediction with Uncertainty Quantification for Water Management: A Constrained Reasoning and Learning Approach. IJCAI 2024: 7269-7277 - [c81]Dina Hussein, Taha Belkhouja, Ganapati Bhat, Janardhan Rao Doppa:
Energy-Efficient Missing Data Imputation in Wearable Health Applications: A Classifier-aware Statistical Approach. IJCAI 2024: 7296-7304 - [c80]Pratyush Dhingra, Jana Doppa, Partha Pratim Pande:
HeTraX: Energy Efficient 3D Heterogeneous Manycore Architecture for Transformer Acceleration. ISLPED 2024: 1-6 - [c79]Ashish Reddy Bommana, Farshad Firouzi, Chukwufumnanya Ogbogu, Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty:
SEC-CiM: Selective Error Compensation for ReRAM-based Compute-in-Memory*. ITC 2024: 177-186 - [c78]Jaehyun Park, Alish Kanani, Lukas Pfromm, Harsh Sharma, Parth Solanki, Eric Tervo, Janardhan Rao Doppa, Partha Pratim Pande, Ümit Y. Ogras:
Thermal Modeling and Management Challenges in Heterogenous Integration: 2.5D Chiplet Platforms and Beyond. VTS 2024: 1-4 - [i60]Pratyush Dhingra, Chukwufumnanya Ogbogu, Biresh Kumar Joardar, Janardhan Rao Doppa, Ananth Kalyanaraman, Partha Pratim Pande:
FARe: Fault-Aware GNN Training on ReRAM-based PIM Accelerators. CoRR abs/2401.10522 (2024) - [i59]Harsh Sharma, Gaurav Narang, Janardhan Rao Doppa, Ümit Y. Ogras, Partha Pratim Pande:
Dataflow-Aware PIM-Enabled Manycore Architecture for Deep Learning Workloads. CoRR abs/2403.19073 (2024) - [i58]Yassine Chemingui, Aryan Deshwal, Trong Nghia Hoang, Janardhan Rao Doppa:
Offline Model-Based Optimization via Policy-Guided Gradient Search. CoRR abs/2405.05349 (2024) - [i57]Mohammed Amine Gharsallaoui, Bhupinderjeet Singh, Supriya Savalkar, Aryan Deshwal, Yan Yan, Ananth Kalyanaraman, Kirti Rajagopalan, Janardhan Rao Doppa:
Streamflow Prediction with Uncertainty Quantification for Water Management: A Constrained Reasoning and Learning Approach. CoRR abs/2406.00133 (2024) - [i56]Ovishake Sen, Chukwufumnanya Ogbogu, Peyman Dehghanzadeh, Janardhan Rao Doppa, Swarup Bhunia, Partha Pratim Pande, Baibhab Chatterjee:
Scalable and Programmable Look-Up Table based Neural Acceleration (LUT-NA) for Extreme Energy Efficiency. CoRR abs/2406.05282 (2024) - [i55]Yuanjie Shi, Subhankar Ghosh, Taha Belkhouja, Janardhan Rao Doppa, Yan Yan:
Conformal Prediction for Class-wise Coverage via Augmented Label Rank Calibration. CoRR abs/2406.06818 (2024) - [i54]Alaleh Ahmadianshalchi, Syrine Belakaria, Janardhan Rao Doppa:
Pareto Front-Diverse Batch Multi-Objective Bayesian Optimization. CoRR abs/2406.08799 (2024) - [i53]Syrine Belakaria, Benjamin Letham, Janardhan Rao Doppa, Barbara Engelhardt, Stefano Ermon, Eytan Bakshy:
Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes. CoRR abs/2407.09739 (2024) - [i52]Pratyush Dhingra, Janardhan Rao Doppa, Partha Pratim Pande:
HeTraX: Energy Efficient 3D Heterogeneous Manycore Architecture for Transformer Acceleration. CoRR abs/2408.03397 (2024) - [i51]Lukas Pfromm, Alish Kanani, Harsh Sharma, Parth Solanki, Eric Tervo, Jaehyun Park, Janardhan Rao Doppa, Partha Pratim Pande, Ümit Y. Ogras:
MFIT: Multi-Fidelity Thermal Modeling for 2.5D and 3D Multi-Chiplet Architectures. CoRR abs/2410.09188 (2024) - [i50]Syrine Belakaria, Alaleh Ahmadianshalchi, Barbara Engelhardt, Stefano Ermon, Janardhan Rao Doppa:
Non-Myopic Multi-Objective Bayesian Optimization. CoRR abs/2412.08085 (2024) - [i49]Yassine Chemingui, Aryan Deshwal, Honghao Wei, Alan Fern, Janardhan Rao Doppa:
Constraint-Adaptive Policy Switching for Offline Safe Reinforcement Learning. CoRR abs/2412.18946 (2024) - 2023
- [j43]Taha Belkhouja, Yan Yan, Janardhan Rao Doppa:
Dynamic Time Warping Based Adversarial Framework for Time-Series Domain. IEEE Trans. Pattern Anal. Mach. Intell. 45(6): 7353-7366 (2023) - [j42]Garrett Wilson, Janardhan Rao Doppa, Diane J. Cook:
CALDA: Improving Multi-Source Time Series Domain Adaptation With Contrastive Adversarial Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 14208-14221 (2023) - [j41]Xiaoxuan Yang, Huanrui Yang, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty, Hai Li:
ESSENCE: Exploiting Structured Stochastic Gradient Pruning for Endurance-Aware ReRAM-Based In-Memory Training Systems. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(7): 2187-2199 (2023) - [j40]Chukwufumnanya Ogbogu, Aqeeb Iqbal Arka, Lukas Pfromm, Biresh Kumar Joardar, Janardhan Rao Doppa, Krishnendu Chakrabarty, Partha Pratim Pande:
Accelerating Graph Neural Network Training on ReRAM-Based PIM Architectures via Graph and Model Pruning. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(8): 2703-2716 (2023) - [j39]Harsh Sharma, Lukas Pfromm, Rasit Onur Topaloglu, Janardhan Rao Doppa, Ümit Y. Ogras, Ananth Kalyanaraman, Partha Pratim Pande:
Florets for Chiplets: Data Flow-aware High-Performance and Energy-efficient Network-on-Interposer for CNN Inference Tasks. ACM Trans. Embed. Comput. Syst. 22(5s): 132:1-132:21 (2023) - [j38]Biresh Kumar Joardar, Janardhan Rao Doppa, Hai (Helen) Li, Krishnendu Chakrabarty, Partha Pratim Pande:
ReaLPrune: ReRAM Crossbar-Aware Lottery Ticket Pruning for CNNs. IEEE Trans. Emerg. Top. Comput. 11(2): 303-317 (2023) - [j37]Gaurav Narang, Aryan Deshwal, Raid Ayoub, Michael Kishinevsky, Janardhan Rao Doppa, Partha Pratim Pande:
Dynamic Power Management in Large Manycore Systems: A Learning-to-Search Framework. ACM Trans. Design Autom. Electr. Syst. 28(5): 84:1-84:21 (2023) - [c77]Subhankar Ghosh, Taha Belkhouja, Yan Yan, Janardhan Rao Doppa:
Improving Uncertainty Quantification of Deep Classifiers via Neighborhood Conformal Prediction: Novel Algorithm and Theoretical Analysis. AAAI 2023: 7722-7730 - [c76]Aryan Deshwal, Sebastian Ament, Maximilian Balandat, Eytan Bakshy, Janardhan Rao Doppa, David Eriksson:
Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings. AISTATS 2023: 7021-7039 - [c75]Syrine Belakaria, Janardhan Rao Doppa, Nicolò Fusi, Rishit Sheth:
Bayesian Optimization Over Iterative Learners with Structured Responses: A Budget-aware Planning Approach. AISTATS 2023: 9076-9093 - [c74]Harsh Sharma, Sumit K. Mandal, Janardhan Rao Doppa, Ümit Y. Ogras, Partha Pratim Pande:
Achieving Datacenter-scale Performance through Chiplet-based Manycore Architectures. DATE 2023: 1-6 - [c73]Chung-Hsuan Tung, Biresh Kumar Joardar, Partha Pratim Pande, Janardhan Rao Doppa, Hai Helen Li, Krishnendu Chakrabarty:
Dynamic Task Remapping for Reliable CNN Training on ReRAM Crossbars. DATE 2023: 1-6 - [c72]Ching-Yuan Chen, Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty:
Attacking Memristor-Mapped Graph Neural Network by Inducing Slow-to-Write Errors. ETS 2023: 1-4 - [c71]Taha Belkhouja, Janardhan Rao Doppa:
Adversarial Framework with Certified Robustness for Time-Series Domain via Statistical Features (Extended Abstract). IJCAI 2023: 6845-6850 - [c70]Dina Hussein, Taha Belkhouja, Ganapati Bhat, Janardhan Rao Doppa:
Energy-Efficient Missing Data Recovery in Wearable Devices: A Novel Search-Based Approach. ISLPED 2023: 1-6 - [c69]Gaurav Narang, Raid Ayoub, Michael Kishinevsky, Janardhan Rao Doppa, Partha Pratim Pande:
Uncertainty-Aware Online Learning for Dynamic Power Management in Large Manycore Systems. ISLPED 2023: 1-6 - [c68]Chukwufumnanya Ogbogu, Soumen Mohapatra, Biresh Kumar Joardar, Janardhan Rao Doppa, Deuk Heo, Krishnendu Chakrabarty, Partha Pratim Pande:
Energy-Efficient ReRAM-Based ML Training via Mixed Pruning and Reconfigurable ADC. ISLPED 2023: 1-6 - [c67]Subhankar Ghosh, Yuanjie Shi, Taha Belkhouja, Yan Yan, Jana Doppa, Brian Jones:
Probabilistically robust conformal prediction. UAI 2023: 681-690 - [e1]Jana Doppa, Swarup Bhunia:
International Conference on Compilers, Architecture, and Synthesis for Embedded Systems, CASES 2023, Hamburg, Germany, September 17-22, 2023. ACM/IEEE 2023, ISBN 979-8-4007-0290-7 [contents] - [i48]Aryan Deshwal, Sebastian Ament, Maximilian Balandat, Eytan Bakshy, Janardhan Rao Doppa, David Eriksson:
Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings. CoRR abs/2303.01774 (2023) - [i47]Subhankar Ghosh, Taha Belkhouja, Yan Yan, Janardhan Rao Doppa:
Improving Uncertainty Quantification of Deep Classifiers via Neighborhood Conformal Prediction: Novel Algorithm and Theoretical Analysis. CoRR abs/2303.10694 (2023) - [i46]Alaleh Ahmadianshalchi, Syrine Belakaria, Janardhan Rao Doppa:
Preference-Aware Constrained Multi-Objective Bayesian Optimization. CoRR abs/2303.13034 (2023) - [i45]Subhankar Ghosh, Yuanjie Shi, Taha Belkhouja, Yan Yan, Jana Doppa, Brian Jones:
Probabilistically robust conformal prediction. CoRR abs/2307.16360 (2023) - [i44]Xueying Wu, Edward Hanson, Nansu Wang, Qilin Zheng, Xiaoxuan Yang, Huanrui Yang, Shiyu Li, Feng Cheng, Partha Pratim Pande, Janardhan Rao Doppa, Krishnendu Chakrabarty, Hai Li:
Block-Wise Mixed-Precision Quantization: Enabling High Efficiency for Practical ReRAM-based DNN Accelerators. CoRR abs/2310.12182 (2023) - [i43]Harsh Sharma, Pratyush Dhingra, Janardhan Rao Doppa, Ümit Y. Ogras, Partha Pratim Pande:
A Heterogeneous Chiplet Architecture for Accelerating End-to-End Transformer Models. CoRR abs/2312.11750 (2023) - 2022
- [j36]Taha Belkhouja, Janardhan Rao Doppa:
Adversarial Framework with Certified Robustness for Time-Series Domain via Statistical Features. J. Artif. Intell. Res. 73: 1435-1471 (2022) - [j35]Biresh Kumar Joardar, Aryan Deshwal, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty:
High-Throughput Training of Deep CNNs on ReRAM-Based Heterogeneous Architectures via Optimized Normalization Layers. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(5): 1537-1549 (2022) - [j34]Chukwufumnanya Ogbogu, Aqeeb Iqbal Arka, Biresh Kumar Joardar, Janardhan Rao Doppa, Hai Helen Li, Krishnendu Chakrabarty, Partha Pratim Pande:
Accelerating Large-Scale Graph Neural Network Training on Crossbar Diet. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(11): 3626-3637 (2022) - [j33]Harsh Sharma, Sumit K. Mandal, Janardhan Rao Doppa, Ümit Y. Ogras, Partha Pratim Pande:
SWAP: A Server-Scale Communication-Aware Chiplet-Based Manycore PIM Accelerator. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(11): 4145-4156 (2022) - [c66]Taha Belkhouja, Yan Yan, Janardhan Rao Doppa:
Training Robust Deep Models for Time-Series Domain: Novel Algorithms and Theoretical Analysis. AAAI 2022: 6055-6063 - [c65]Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa, Dae Hyun Kim:
Bayesian Optimization over Permutation Spaces. AAAI 2022: 6515-6523 - [c64]Dina Hussein, Ganapati Bhat, Janardhan Rao Doppa:
Adaptive Energy Management for Self-Sustainable Wearables in Mobile Health. AAAI 2022: 11935-11944 - [c63]Nuzhat Yamin, Ganapati Bhat, Janardhan Rao Doppa:
DIET: A Dynamic Energy Management Approach for Wearable Health Monitoring Devices. DATE 2022: 1365-1370 - [c62]Dina Hussein, Taha Belkhouja, Ganapati Bhat, Janardhan Rao Doppa:
Reliable Machine Learning for Wearable Activity Monitoring: Novel Algorithms and Theoretical Guarantees. ICCAD 2022: 33:1-33:9 - [c61]Biresh Kumar Joardar, Aqeeb Iqbal Arka, Janardhan Rao Doppa, Partha Pratim Pande:
Fault-Tolerant Deep Learning Using Regularization. ICCAD 2022: 159:1-159:6 - [c60]Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty:
NoC-enabled 3D Heterogeneous Manycore Systems for Big-Data Applications. ISQED 2022: 1-6 - [i42]Dina Hussein, Ganapati Bhat, Janardhan Rao Doppa:
Adaptive Energy Management for Self-Sustainable Wearables in Mobile Health. CoRR abs/2201.07888 (2022) - [i41]Syrine Belakaria, Aryan Deshwal, Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa:
Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization. CoRR abs/2204.05944 (2022) - [i40]Syrine Belakaria, Rishit Sheth, Janardhan Rao Doppa, Nicolò Fusi:
Bayesian Optimization Over Iterative Learners with Structured Responses: A Budget-aware Planning Approach. CoRR abs/2206.12708 (2022) - [i39]Taha Belkhouja, Yan Yan, Janardhan Rao Doppa:
Training Robust Deep Models for Time-Series Domain: Novel Algorithms and Theoretical Analysis. CoRR abs/2207.04305 (2022) - [i38]Taha Belkhouja, Yan Yan, Janardhan Rao Doppa:
Out-of-Distribution Detection in Time-Series Domain: A Novel Seasonal Ratio Scoring Approach. CoRR abs/2207.04306 (2022) - [i37]Taha Belkhouja, Janardhan Rao Doppa:
Adversarial Framework with Certified Robustness for Time-Series Domain via Statistical Features. CoRR abs/2207.04307 (2022) - [i36]Taha Belkhouja, Yan Yan, Janardhan Rao Doppa:
Dynamic Time Warping based Adversarial Framework for Time-Series Domain. CoRR abs/2207.04308 (2022) - [i35]Garrett Wilson, Janardhan Rao Doppa, Diane J. Cook:
Domain Adaptation Under Behavioral and Temporal Shifts for Natural Time Series Mobile Activity Recognition. CoRR abs/2207.04367 (2022) - [i34]Harsha Kokel, Mayukh Das, Md. Rakibul Islam, Julia Bonn, Jon Z. Cai, Soham Dan, Anjali Narayan-Chen, Prashant Jayannavar, Janardhan Rao Doppa, Julia Hockenmaier, Sriraam Natarajan, Martha Palmer, Dan Roth:
Human-guided Collaborative Problem Solving: A Natural Language based Framework. CoRR abs/2207.09566 (2022) - 2021
- [j32]Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa:
Output Space Entropy Search Framework for Multi-Objective Bayesian Optimization. J. Artif. Intell. Res. 72: 667-715 (2021) - [j31]Anwesha Chatterjee, Shouvik Musavvir, Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande:
Power Management of Monolithic 3D Manycore Chips with Inter-tier Process Variations. ACM J. Emerg. Technol. Comput. Syst. 17(2): 13:1-13:19 (2021) - [j30]Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande, Hai Li, Krishnendu Chakrabarty:
AccuReD: High Accuracy Training of CNNs on ReRAM/GPU Heterogeneous 3-D Architecture. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 40(5): 971-984 (2021) - [j29]Biresh Kumar Joardar, Janardhan Rao Doppa, Hai Li, Krishnendu Chakrabarty, Partha Pratim Pande:
Learning to Train CNNs on Faulty ReRAM-based Manycore Accelerators. ACM Trans. Embed. Comput. Syst. 20(5s): 55:1-55:23 (2021) - [j28]Aqeeb Iqbal Arka, Biresh Kumar Joardar, Ryan Gary Kim, Dae Hyun Kim, Janardhan Rao Doppa, Partha Pratim Pande:
HeM3D: Heterogeneous Manycore Architecture Based on Monolithic 3D Vertical Integration. ACM Trans. Design Autom. Electr. Syst. 26(2): 16:1-16:21 (2021) - [j27]Aqeeb Iqbal Arka, Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty:
Performance and Accuracy Tradeoffs for Training Graph Neural Networks on ReRAM-Based Architectures. IEEE Trans. Very Large Scale Integr. Syst. 29(10): 1743-1756 (2021) - [c59]Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa:
Mercer Features for Efficient Combinatorial Bayesian Optimization. AAAI 2021: 7210-7218 - [c58]Aryan Deshwal, Syrine Belakaria, Ganapati Bhat, Janardhan Rao Doppa, Partha Pratim Pande:
Learning Pareto-Frontier Resource Management Policies for Heterogeneous SoCs: An Information-Theoretic Approach. DAC 2021: 607-612 - [c57]Biresh Kumar Joardar, Aqeeb Iqbal Arka, Janardhan Rao Doppa, Partha Pratim Pande:
3D++: Unlocking the Next Generation of High-Performance and Energy-Efficient Architectures using M3D Integration. DATE 2021: 158-163 - [c56]Aqeeb Iqbal Arka, Janardhan Rao Doppa, Partha Pratim Pande, Biresh Kumar Joardar, Krishnendu Chakrabarty:
ReGraphX: NoC-enabled 3D Heterogeneous ReRAM Architecture for Training Graph Neural Networks. DATE 2021: 1667-1672 - [c55]Aqeeb Iqbal Arka, Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty:
DARe: DropLayer-Aware Manycore ReRAM architecture for Training Graph Neural Networks. ICCAD 2021: 1-9 - [c54]Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa, Partha Pratim Pande:
A General Hardware and Software Co-Design Framework for Energy-Efficient Edge AI. ICCAD 2021: 1-7 - [c53]Biresh Kumar Joardar, Aqeeb Iqbal Arka, Janardhan Rao Doppa, Partha Pratim Pande, Hai Li, Krishnendu Chakrabarty:
Heterogeneous Manycore Architectures Enabled by Processing-in-Memory for Deep Learning: From CNNs to GNNs: (ICCAD Special Session Paper). ICCAD 2021: 1-7 - [c52]Xiaoxuan Yang, Syrine Belakaria, Biresh Kumar Joardar, Huanrui Yang, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty, Hai Helen Li:
Multi-Objective Optimization of ReRAM Crossbars for Robust DNN Inferencing under Stochastic Noise. ICCAD 2021: 1-9 - [c51]Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa:
Bayesian Optimization over Hybrid Spaces. ICML 2021: 2632-2643 - [c50]Janardhan Rao Doppa:
Adaptive Experimental Design for Optimizing Combinatorial Structures. IJCAI 2021: 4940-4945 - [c49]Aryan Deshwal, Janardhan Rao Doppa:
Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces. NeurIPS 2021: 8185-8200 - [i33]Aqeeb Iqbal Arka, Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty:
ReGraphX: NoC-enabled 3D Heterogeneous ReRAM Architecture for Training Graph Neural Networks. CoRR abs/2102.07959 (2021) - [i32]Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa, Partha Pratim Pande:
SETGAN: Scale and Energy Trade-off GANs for Image Applications on Mobile Platforms. CoRR abs/2103.12896 (2021) - [i31]Aryan Deshwal, Syrine Belakaria, Ganapati Bhat, Janardhan Rao Doppa, Partha Pratim Pande:
Learning Pareto-Frontier Resource Management Policies for Heterogeneous SoCs: An Information-Theoretic Approach. CoRR abs/2105.09282 (2021) - [i30]Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa:
Bayesian Optimization over Hybrid Spaces. CoRR abs/2106.04682 (2021) - [i29]Xiaoxuan Yang, Syrine Belakaria, Biresh Kumar Joardar, Huanrui Yang, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty, Hai Li:
Multi-Objective Optimization of ReRAM Crossbars for Robust DNN Inferencing under Stochastic Noise. CoRR abs/2109.05437 (2021) - [i28]Garrett Wilson, Janardhan Rao Doppa, Diane J. Cook:
CALDA: Improving Multi-Source Time Series Domain Adaptation with Contrastive Adversarial Learning. CoRR abs/2109.14778 (2021) - [i27]Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa:
Output Space Entropy Search Framework for Multi-Objective Bayesian Optimization. CoRR abs/2110.06980 (2021) - [i26]Aryan Deshwal, Janardhan Rao Doppa:
Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces. CoRR abs/2111.01186 (2021) - [i25]Biresh Kumar Joardar, Janardhan Rao Doppa, Hai Li, Krishnendu Chakrabarty, Partha Pratim Pande:
ReaLPrune: ReRAM Crossbar-aware Lottery Ticket Pruned CNNs. CoRR abs/2111.09272 (2021) - [i24]Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa, Dae Hyun Kim:
Bayesian Optimization over Permutation Spaces. CoRR abs/2112.01049 (2021) - 2020
- [j26]Mayukh Das, Nandini Ramanan, Janardhan Rao Doppa, Sriraam Natarajan:
Few-Shot Induction of Generalized Logical Concepts via Human Guidance. Frontiers Robotics AI 7: 122 (2020) - [j25]Bing Li, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty, Joe X. Qiu, Hai (Helen) Li:
3D-ReG: A 3D ReRAM-based Heterogeneous Architecture for Training Deep Neural Networks. ACM J. Emerg. Technol. Comput. Syst. 16(2): 20:1-20:24 (2020) - [j24]Aqeeb Iqbal Arka, Srinivasan Gopal, Janardhan Rao Doppa, Deukhyoun Heo, Partha Pratim Pande:
Making a Case for Partially Connected 3D NoC: NFIC versus TSV. ACM J. Emerg. Technol. Comput. Syst. 16(4): 41:1-41:17 (2020) - [j23]Taha Belkhouja, Janardhan Rao Doppa:
Analyzing Deep Learning for Time-Series Data Through Adversarial Lens in Mobile and IoT Applications. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(11): 3190-3201 (2020) - [j22]Nitthilan Kanappan Jayakodi, Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa:
Design and Optimization of Energy-Accuracy Tradeoff Networks for Mobile Platforms via Pretrained Deep Models. ACM Trans. Embed. Comput. Syst. 19(1): 4:1-4:24 (2020) - [j21]Sumit K. Mandal, Ganapati Bhat, Janardhan Rao Doppa, Partha Pratim Pande, Ümit Y. Ogras:
An Energy-aware Online Learning Framework for Resource Management in Heterogeneous Platforms. ACM Trans. Design Autom. Electr. Syst. 25(3): 28:1-28:26 (2020) - [c48]Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa, Alan Fern:
Optimizing Discrete Spaces via Expensive Evaluations: A Learning to Search Framework. AAAI 2020: 3773-3780 - [c47]Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa:
Multi-Fidelity Multi-Objective Bayesian Optimization: An Output Space Entropy Search Approach. AAAI 2020: 10035-10043 - [c46]Syrine Belakaria, Aryan Deshwal, Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa:
Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization. AAAI 2020: 10044-10052 - [c45]Nitthilan Kanappan Jayakodi, Janardhan Rao Doppa, Partha Pratim Pande:
PETNet: Polycount and Energy Trade-off Deep Networks for Producing 3D Objects from Images. DAC 2020: 1-6 - [c44]Sumit K. Mandal, Ümit Y. Ogras, Janardhan Rao Doppa, Raid Zuhair Ayoub, Michael Kishinevsky, Partha Pratim Pande:
Online Adaptive Learning for Runtime Resource Management of Heterogeneous SoCs. DAC 2020: 1-6 - [c43]Biresh Kumar Joardar, Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa, Hai Li, Partha Pratim Pande, Krishnendu Chakrabarty:
GRAMARCH: A GPU-ReRAM based Heterogeneous Architecture for Neural Image Segmentation. DATE 2020: 228-233 - [c42]Zhiyuan Zhou, Syrine Belakaria, Aryan Deshwal, Wookpyo Hong, Janardhan Rao Doppa, Partha Pratim Pande, Deukhyoun Heo:
Design of Multi-Output Switched-Capacitor Voltage Regulator via Machine Learning. DATE 2020: 502-507 - [c41]Shouvik Musavvir, Anwesha Chatterjee, Ryan Gary Kim, Dae Hyun Kim, Janardhan Rao Doppa, Partha Pratim Pande:
Power, Performance, and Thermal Trade-offs in M3D-enabled Manycore Chips. DATE 2020: 1752-1757 - [c40]Nitthilan Kanappan Jayakodi, Janardhan Rao Doppa, Partha Pratim Pande:
SETGAN: Scale and Energy Trade-off GANs for Image Applications on Mobile Platforms. ICCAD 2020: 23:1-23:9 - [c39]Garrett Wilson, Janardhan Rao Doppa, Diane J. Cook:
Multi-Source Deep Domain Adaptation with Weak Supervision for Time-Series Sensor Data. KDD 2020: 1768-1778 - [i23]Sumit K. Mandal, Ganapati Bhat, Janardhan Rao Doppa, Partha Pratim Pande, Ümit Y. Ogras:
An Energy-Aware Online Learning Framework for Resource Management in Heterogeneous Platforms. CoRR abs/2003.09526 (2020) - [i22]Garrett Wilson, Janardhan Rao Doppa, Diane J. Cook:
Multi-Source Deep Domain Adaptation with Weak Supervision for Time-Series Sensor Data. CoRR abs/2005.10996 (2020) - [i21]Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa:
Uncertainty aware Search Framework for Multi-Objective Bayesian Optimization with Constraints. CoRR abs/2008.07029 (2020) - [i20]Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa:
Scalable Combinatorial Bayesian Optimization with Tractable Statistical models. CoRR abs/2008.08177 (2020) - [i19]Sumit K. Mandal, Ümit Y. Ogras, Janardhan Rao Doppa, Raid Zuhair Ayoub, Michael Kishinevsky, Partha Pratim Pande:
Online Adaptive Learning for Runtime Resource Management of Heterogeneous SoCs. CoRR abs/2008.09728 (2020) - [i18]Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa:
Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints. CoRR abs/2009.01721 (2020) - [i17]Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa:
Information-Theoretic Multi-Objective Bayesian Optimization with Continuous Approximations. CoRR abs/2009.05700 (2020) - [i16]Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa:
Multi-Fidelity Multi-Objective Bayesian Optimization: An Output Space Entropy Search Approach. CoRR abs/2011.01542 (2020) - [i15]Aqeeb Iqbal Arka, Biresh Kumar Joardar, Ryan Gary Kim, Dae Hyun Kim, Janardhan Rao Doppa, Partha Pratim Pande:
HeM3D: Heterogeneous Manycore Architecture Based on Monolithic 3D Vertical Integration. CoRR abs/2012.00102 (2020) - [i14]Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa, Alan Fern:
Optimizing Discrete Spaces via Expensive Evaluations: A Learning to Search Framework. CoRR abs/2012.07320 (2020) - [i13]Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa:
Mercer Features for Efficient Combinatorial Bayesian Optimization. CoRR abs/2012.07762 (2020)
2010 – 2019
- 2019
- [j20]Janardhan Rao Doppa, Justinian Rosca, Paul Bogdan:
Guest Editors' Introduction: Special Issue on Smart and Autonomous Systems for Sustainability. IEEE Des. Test 36(5): 5-6 (2019) - [j19]Janardhan Rao Doppa, Justinian Rosca, Paul Bogdan:
Autonomous Design Space Exploration of Computing Systems for Sustainability: Opportunities and Challenges. IEEE Des. Test 36(5): 35-43 (2019) - [j18]Mayukh Das, Phillip Odom, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan:
Planning with actively eliciting preferences. Knowl. Based Syst. 165: 219-227 (2019) - [j17]Biresh Kumar Joardar, Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande, Diana Marculescu, Radu Marculescu:
Learning-Based Application-Agnostic 3D NoC Design for Heterogeneous Manycore Systems. IEEE Trans. Computers 68(6): 852-866 (2019) - [j16]Aryan Deshwal, Nitthilan Kannappan Jayakodi, Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande:
MOOS: A Multi-Objective Design Space Exploration and Optimization Framework for NoC Enabled Manycore Systems. ACM Trans. Embed. Comput. Syst. 18(5s): 77:1-77:23 (2019) - [j15]Dongjin Lee, Sourav Das, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty:
Impact of Electrostatic Coupling on Monolithic 3D-enabled Network on Chip. ACM Trans. Design Autom. Electr. Syst. 24(6): 62:1-62:22 (2019) - [j14]Sumit K. Mandal, Ganapati Bhat, Chetan Arvind Patil, Janardhan Rao Doppa, Partha Pratim Pande, Ümit Y. Ogras:
Dynamic Resource Management of Heterogeneous Mobile Platforms via Imitation Learning. IEEE Trans. Very Large Scale Integr. Syst. 27(12): 2842-2854 (2019) - [c38]Paul Bogdan, Fan Chen, Aryan Deshwal, Janardhan Rao Doppa, Biresh Kumar Joardar, Hai (Helen) Li, Shahin Nazarian, Linghao Song, Yao Xiao:
Taming extreme heterogeneity via machine learning based design of autonomous manycore systems. CODES+ISSS 2019: 21:1-21:10 - [c37]Biresh Kumar Joardar, Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande:
Design and Optimization of Heterogeneous Manycore Systems Enabled by Emerging Interconnect Technologies: Promises and Challenges. DATE 2019: 138-143 - [c36]Biresh Kumar Joardar, Bing Li, Janardhan Rao Doppa, Hai Li, Partha Pratim Pande, Krishnendu Chakrabarty:
REGENT: A Heterogeneous ReRAM/GPU-based Architecture Enabled by NoC for Training CNNs. DATE 2019: 522-527 - [c35]Chao Ma, F. A. Rezaur Rahman Chowdhury, Aryan Deshwal, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth:
Randomized Greedy Search for Structured Prediction: Amortized Inference and Learning. IJCAI 2019: 5130-5138 - [c34]Aryan Deshwal, Janardhan Rao Doppa, Dan Roth:
Learning and Inference for Structured Prediction: A Unifying Perspective. IJCAI 2019: 6291-6299 - [c33]Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa:
Max-value Entropy Search for Multi-Objective Bayesian Optimization. NeurIPS 2019: 7823-7833 - [i12]Shubhomoy Das, Md. Rakibul Islam, Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa:
Active Anomaly Detection via Ensembles: Insights, Algorithms, and Interpretability. CoRR abs/1901.08930 (2019) - [i11]Nitthilan Kannappan Jayakodi, Anwesha Chatterjee, Wonje Choi, Janardhan Rao Doppa, Partha Pratim Pande:
Trading-off Accuracy and Energy of Deep Inference on Embedded Systems: A Co-Design Approach. CoRR abs/1901.10584 (2019) - [i10]Mayukh Das, Nandini Ramanan, Janardhan Rao Doppa, Sriraam Natarajan:
One-Shot Induction of Generalized Logical Concepts via Human Guidance. CoRR abs/1912.07060 (2019) - 2018
- [j13]Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande, Diana Marculescu, Radu Marculescu:
Machine Learning and Manycore Systems Design: A Serendipitous Symbiosis. Computer 51(7): 66-77 (2018) - [j12]Dongjin Lee, Sourav Das, Dae Hyun Kim, Janardhan Rao Doppa, Partha Pratim Pande:
Design Space Exploration of 3D Network-on-Chip: A Sensitivity-based Optimization Approach. ACM J. Emerg. Technol. Comput. Syst. 14(3): 32:1-32:26 (2018) - [j11]Wonje Choi, Karthi Duraisamy, Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande, Diana Marculescu, Radu Marculescu:
On-Chip Communication Network for Efficient Training of Deep Convolutional Networks on Heterogeneous Manycore Systems. IEEE Trans. Computers 67(5): 672-686 (2018) - [j10]Nitthilan Kannappan Jayakodi, Anwesha Chatterjee, Wonje Choi, Janardhan Rao Doppa, Partha Pratim Pande:
Trading-Off Accuracy and Energy of Deep Inference on Embedded Systems: A Co-Design Approach. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 37(11): 2881-2893 (2018) - [j9]Dongjin Lee, Sourav Das, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty:
Performance and Thermal Tradeoffs for Energy-Efficient Monolithic 3D Network-on-Chip. ACM Trans. Design Autom. Electr. Syst. 23(5): 60:1-60:25 (2018) - [j8]Xian Li, Karthi Duraisamy, Paul Bogdan, Janardhan Rao Doppa, Partha Pratim Pande:
Scalable Network-on-Chip Architectures for Brain-Machine Interface Applications. IEEE Trans. Very Large Scale Integr. Syst. 26(10): 1895-1907 (2018) - [c32]Ellis Hoag, Janardhan Rao Doppa:
Bayesian Optimization Meets Search Based Optimization: A Hybrid Approach for Multi-Fidelity Optimization. AAAI 2018: 8085-8086 - [c31]Mayukh Das, Phillip Odom, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan:
Preference-Guided Planning: An Active Elicitation Approach. AAMAS 2018: 1921-1923 - [c30]Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande:
Machine learning for design space exploration and optimization of manycore systems. ICCAD 2018: 48 - [c29]Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande, Diana Marculescu, Radu Marculescu:
Hybrid on-chip communication architectures for heterogeneous manycore systems. ICCAD 2018: 62 - [c28]Sourav Das, Kanad Basu, Janardhan Rao Doppa, Partha Pratim Pande, Ramesh Karri, Krishnendu Chakrabarty:
Abetting Planned Obsolescence by Aging 3D Networks-on-Chip. NOCS 2018: 10:1-10:8 - [i9]Mohammad Hossein Namaki, F. A. Rezaur Rahman Chowdhury, Md. Rakibul Islam, Janardhan Rao Doppa, Yinghui Wu:
Learning to Speed Up Query Planning in Graph Databases. CoRR abs/1801.06766 (2018) - [i8]Mayukh Das, Phillip Odom, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan:
Preference-Guided Planning: An Active Elicitation Approach. CoRR abs/1804.07404 (2018) - [i7]John Walker Orr, Prasad Tadepalli, Janardhan Rao Doppa, Xiaoli Z. Fern, Thomas G. Dietterich:
Learning Scripts as Hidden Markov Models. CoRR abs/1809.03680 (2018) - [i6]Shubhomoy Das, Md. Rakibul Islam, Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa:
Active Anomaly Detection via Ensembles. CoRR abs/1809.06477 (2018) - [i5]Shubhomoy Das, Janardhan Rao Doppa:
GLAD: GLocalized Anomaly Detection via Active Feature Space Suppression. CoRR abs/1810.01403 (2018) - [i4]Biresh Kumar Joardar, Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande, Diana Marculescu, Radu Marculescu:
Learning-based Application-Agnostic 3D NoC Design for Heterogeneous Manycore Systems. CoRR abs/1810.08869 (2018) - 2017
- [j7]Sourav Das, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty:
Design-Space Exploration and Optimization of an Energy-Efficient and Reliable 3-D Small-World Network-on-Chip. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 36(5): 719-732 (2017) - [j6]Bryan David Minor, Janardhan Rao Doppa, Diane J. Cook:
Learning Activity Predictors from Sensor Data: Algorithms, Evaluation, and Applications. IEEE Trans. Knowl. Data Eng. 29(12): 2744-2757 (2017) - [j5]Sourav Das, Dongjin Lee, Wonje Choi, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty:
VFI-Based Power Management to Enhance the Lifetime of High-Performance 3D NoCs. ACM Trans. Design Autom. Electr. Syst. 23(1): 7:1-7:26 (2017) - [j4]Ryan Gary Kim, Wonje Choi, Zhuo Chen, Janardhan Rao Doppa, Partha Pratim Pande, Diana Marculescu, Radu Marculescu:
Imitation Learning for Dynamic VFI Control in Large-Scale Manycore Systems. IEEE Trans. Very Large Scale Integr. Syst. 25(9): 2458-2471 (2017) - [c27]Mayukh Das, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan:
Active Preference Elicitation for Planning. AAAI Workshops 2017 - [c26]Anjali Narayan-Chen, Colin Graber, Mayukh Das, Md. Rakibul Islam, Soham Dan, Sriraam Natarajan, Janardhan Rao Doppa, Julia Hockenmaier, Martha Palmer, Dan Roth:
Towards Problem Solving Agents that Communicate and Learn. RoboNLP@ACL 2017: 95-103 - [c25]F. A. Rezaur Rahman Chowdhury, Chao Ma, Md. Rakibul Islam, Mohammad Hossein Namaki, Mohammad Omar Faruk, Janardhan Rao Doppa:
Select-and-Evaluate: A Learning Framework for Large-Scale Knowledge Graph Search. ACML 2017: 129-144 - [c24]Chao Ma, Janardhan Rao Doppa, Prasad Tadepalli, Hamed Shahbazi, Xiaoli Z. Fern:
Multi-Task Structured Prediction for Entity Analysis: Search-Based Learning Algorithms. ACML 2017: 514-529 - [c23]Mohammad Hossein Namaki, F. A. Rezaur Rahman Chowdhury, Md. Rakibul Islam, Janardhan Rao Doppa, Yinghui Wu:
Learning to Speed Up Query Planning in Graph Databases. ICAPS 2017: 443-451 - [c22]Sudeep Pasricha, Janardhan Rao Doppa, Krishnendu Chakrabarty, Saideep Tiku, Daniel Dauwe, Shi Jin, Partha Pratim Pande:
Data analytics enables energy-efficiency and robustness: from mobile to manycores, datacenters, and networks (special session paper). CODES+ISSS 2017: 27:1-27:10 - [c21]Sourav Das, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty:
Robust TSV-based 3D NoC design to counteract electromigration and crosstalk noise. DATE 2017: 1366-1371 - [c20]Sourav Das, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty:
Monolithic 3D-Enabled High Performance and Energy Efficient Network-on-Chip. ICCD 2017: 233-240 - [c19]Biresh Kumar Joardar, Wonje Choi, Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande, Diana Marculescu, Radu Marculescu:
3D NoC-Enabled Heterogeneous Manycore Architectures for Accelerating CNN Training: Performance and Thermal Trade-offs. NOCS 2017: 18:1-18:8 - [c18]Janardhan Rao Doppa, Ryan Gary Kim, Mihailo Isakov, Michel A. Kinsy, Hyoukjun Kwon, Tushar Krishna:
Adaptive Manycore Architectures for Big Data Computing. NOCS 2017: 20:1-20:8 - [i3]Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande, Diana Marculescu, Radu Marculescu:
Machine Learning and Manycore Systems Design: A Serendipitous Symbiosis. CoRR abs/1712.00076 (2017) - [i2]Wonje Choi, Karthi Duraisamy, Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande, Diana Marculescu, Radu Marculescu:
On-Chip Communication Network for Efficient Training of Deep Convolutional Networks on Heterogeneous Manycore Systems. CoRR abs/1712.02293 (2017) - 2016
- [c17]Wonje Choi, Karthi Duraisamy, Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande, Radu Marculescu, Diana Marculescu:
Hybrid network-on-chip architectures for accelerating deep learning kernels on heterogeneous manycore platforms. CASES 2016: 13:1-13:10 - [c16]Sourav Das, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty:
Reliability and performance trade-offs for 3D NoC-enabled multicore chips. DATE 2016: 1429-1432 - [c15]Sourav Das, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty:
Energy-efficient and reliable 3D network-on-chip (NoC): architectures and optimization algorithms. ICCAD 2016: 57 - [i1]Sourav Das, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty:
Design-Space Exploration and Optimization of an Energy-Efficient and Reliable 3D Small-world Network-on-Chip. CoRR abs/1608.06972 (2016) - 2015
- [c14]Jun Xie, Chao Ma, Janardhan Rao Doppa, Prashanth Mannem, Xiaoli Z. Fern, Thomas G. Dietterich, Prasad Tadepalli:
Learning Greedy Policies for the Easy-First Framework. AAAI 2015: 2339-2345 - [c13]Michael Lam, Janardhan Rao Doppa, Sinisa Todorovic, Thomas G. Dietterich:
ℋC-search for structured prediction in computer vision. CVPR 2015: 4923-4932 - [c12]Sourav Das, Janardhan Rao Doppa, Daehyun Kim, Partha Pratim Pande, Krishnendu Chakrabarty:
Optimizing 3D NoC Design for Energy Efficiency: A Machine Learning Approach. ICCAD 2015: 705-712 - [c11]Bryan David Minor, Janardhan Rao Doppa, Diane J. Cook:
Data-Driven Activity Prediction: Algorithms, Evaluation Methodology, and Applications. KDD 2015: 805-814 - 2014
- [j3]Janardhan Rao Doppa, Alan Fern, Prasad Tadepalli:
HC-Search: A Learning Framework for Search-based Structured Prediction. J. Artif. Intell. Res. 50: 369-407 (2014) - [j2]Janardhan Rao Doppa, Alan Fern, Prasad Tadepalli:
Structured prediction via output space search. J. Mach. Learn. Res. 15(1): 1317-1350 (2014) - [c10]John Walker Orr, Prasad Tadepalli, Janardhan Rao Doppa, Xiaoli Z. Fern, Thomas G. Dietterich:
Learning Scripts as Hidden Markov Models. AAAI 2014: 1565-1571 - [c9]Janardhan Rao Doppa, Jun Yu, Chao Ma, Alan Fern, Prasad Tadepalli:
HC-Search for Multi-Label Prediction: An Empirical Study. AAAI 2014: 1795-1801 - [c8]Chao Ma, Janardhan Rao Doppa, John Walker Orr, Prashanth Mannem, Xiaoli Z. Fern, Thomas G. Dietterich, Prasad Tadepalli:
Prune-and-Score: Learning for Greedy Coreference Resolution. EMNLP 2014: 2115-2126 - 2013
- [c7]Janardhan Rao Doppa, Alan Fern, Prasad Tadepalli:
HC-Search: Learning Heuristics and Cost Functions for Structured Prediction. AAAI 2013: 253-259 - [c6]Michael Lam, Janardhan Rao Doppa, Xu Hu, Sinisa Todorovic, Thomas G. Dietterich, Abigail Reft, Marymegan Daly:
Learning to Detect Basal Tubules of Nematocysts in SEM Images. ICCV Workshops 2013: 190-196 - 2012
- [j1]Xiaoqin Zhang, Bhavesh Shrestha, Sung Wook Yoon, Subbarao Kambhampati, Phillip DiBona, Jinhong K. Guo, Daniel McFarlane, Martin O. Hofmann, Kenneth R. Whitebread, Darren Scott Appling, Elizabeth T. Whitaker, Ethan Trewhitt, Li Ding, James Michaelis, Deborah L. McGuinness, James A. Hendler, Janardhan Rao Doppa, Charles Parker, Thomas G. Dietterich, Prasad Tadepalli, Weng-Keen Wong, Derek T. Green, Antons Rebguns, Diana F. Spears, Ugur Kuter, Geoffrey Levine, Gerald DeJong, Reid MacTavish, Santiago Ontañón, Jainarayan Radhakrishnan, Ashwin Ram, Hala Mostafa, Huzaifa Zafar, Chongjie Zhang, Daniel D. Corkill, Victor R. Lesser, Zhexuan Song:
An Ensemble Architecture for Learning Complex Problem-Solving Techniques from Demonstration. ACM Trans. Intell. Syst. Technol. 3(4): 75:1-75:38 (2012) - [c5]Janardhan Rao Doppa, Alan Fern, Prasad Tadepalli:
Output Space Search for Structured Prediction. ICML 2012 - 2011
- [c4]Shahed Sorower, Thomas G. Dietterich, Janardhan Rao Doppa, John Walker Orr, Prasad Tadepalli, Xiaoli Z. Fern:
Inverting Grice's Maxims to Learn Rules from Natural Language Extractions. NIPS 2011: 1053-1061 - [c3]Janardhan Rao Doppa, Shahed Sorower, Mohammad NasrEsfahani, John Walker Orr, Thomas G. Dietterich, Xiaoli Z. Fern, Prasad Tadepalli, Jed Irvine:
Learning Rules from Incomplete Examples via Implicit Mention Models. ACML 2011: 197-212 - 2010
- [c2]Janardhan Rao Doppa, Jun Yu, Prasad Tadepalli, Lise Getoor:
Learning Algorithms for Link Prediction Based on Chance Constraints. ECML/PKDD (1) 2010: 344-360
2000 – 2009
- 2009
- [c1]Xiaoqin Zhang, Sung Wook Yoon, Phillip DiBona, Darren Scott Appling, Li Ding, Janardhan Rao Doppa, Derek T. Green, Jinhong K. Guo, Ugur Kuter, Geoffrey Levine, Reid MacTavish, Daniel McFarlane, James Michaelis, Hala Mostafa, Santiago Ontañón, Charles Parker, Jainarayan Radhakrishnan, Antons Rebguns, Bhavesh Shrestha, Zhexuan Song, Ethan Trewhitt, Huzaifa Zafar, Chongjie Zhang, Daniel D. Corkill, Gerald DeJong, Thomas G. Dietterich, Subbarao Kambhampati, Victor R. Lesser, Deborah L. McGuinness, Ashwin Ram, Diana F. Spears, Prasad Tadepalli, Elizabeth T. Whitaker, Weng-Keen Wong, James A. Hendler, Martin O. Hofmann, Kenneth R. Whitebread:
An Ensemble Learning and Problem Solving Architecture for Airspace Management. IAAI 2009
Coauthor Index
Nitthilan Kannappan Jayakodi
aka: Nitthilan Kanappan Jayakodi
aka: Nitthilan Kanappan Jayakodi
[j49] [j48] [j47] [j46] [j44] [c85] [c84] [c80] [c79] [c78] [i60] [i59] [i56] [i52] [i51] [j41] [j40] [j39] [j38] [j37] [c74] [c73] [c72] [c69] [c68] [i44] [i43] [j35] [j34] [j33] [c61] [c60] [j31] [j30] [j29] [j28] [j27] [c58] [c57] [c56] [c55] [c54] [c53] [c52] [i33] [i32] [i31] [i29] [i25] [j25] [j24] [j21] [c45] [c44] [c43] [c42] [c41] [c40] [i23] [i19] [i15] [j17] [j16] [j15] [j14] [c37] [c36] [i11] [j13] [j12] [j11] [j10] [j9] [j8] [c30] [c29] [c28] [i4] [j7] [j5] [j4] [c22] [c21] [c20] [c19] [i3] [i2] [c17] [c16] [c15] [i1] [c12]
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last updated on 2025-01-26 23:47 CET by the dblp team
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