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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
- 2023
[j40]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)- [j39]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) - [j38]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) - [j37]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) - [c74]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 - [c73]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 - [c72]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 - [c71]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 - [c70]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 - [c69]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 - [c68]Taha Belkhouja, Janardhan Rao Doppa:
Adversarial Framework with Certified Robustness for Time-Series Domain via Statistical Features (Extended Abstract). IJCAI 2023: 6845-6850 - [c67]Subhankar Ghosh, Yuanjie Shi, Taha Belkhouja, Yan Yan, Jana Doppa, Brian Jones:
Probabilistically robust conformal prediction. UAI 2023: 681-690 - [i46]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) - [i45]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) - [i44]Alaleh Ahmadianshalchi, Syrine Belakaria, Janardhan Rao Doppa:
Preference-Aware Constrained Multi-Objective Bayesian Optimization. CoRR abs/2303.13034 (2023) - [i43]Subhankar Ghosh, Yuanjie Shi, Taha Belkhouja, Yan Yan, Jana Doppa, Brian Jones:
Probabilistically robust conformal prediction. CoRR abs/2307.16360 (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:
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