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ORCIDKrishna Narra
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2020 – today
- 2024
[c7]Lynn Chua, Qiliang Cui, Badih Ghazi, Charlie Harrison, Pritish Kamath, Walid Krichene, Ravi Kumar, Pasin Manurangsi, Nicolas Mayoraz, Hema Venkata Krishna Giri Narra, Steffen Rendle, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang:
Training Differentially Private Ad Prediction Models With Semi-Sensitive Features. AdKDD@KDD 2024- [i8]Lynn Chua, Qiliang Cui, Badih Ghazi, Charlie Harrison, Pritish Kamath, Walid Krichene, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang:
Training Differentially Private Ad Prediction Models with Semi-Sensitive Features. CoRR abs/2401.15246 (2024) - 2023
- [c6]Carson Denison, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang:
Private Ad Modeling with DP-SGD. AdKDD@KDD 2023 - 2022
- [i7]Carson Denison, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang:
Private Ad Modeling with DP-SGD. CoRR abs/2211.11896 (2022) - 2021
- [c5]Krishna Giri Narra, Zhifeng Lin, Yongqin Wang
, Keshav Balasubramanian, Murali Annavaram:
Origami Inference: Private Inference Using Hardware Enclaves. CLOUD 2021: 78-84 - 2020
- [c4]Hema Venkata Krishna Giri Narra, Zhifeng Lin, Ganesh Ananthanarayanan, Salman Avestimehr, Murali Annavaram:
Collage Inference: Using Coded Redundancy for Lowering Latency Variation in Distributed Image Classification Systems. ICDCS 2020: 453-463
2010 – 2019
- 2019
- [c3]Krishna Giri Narra, Zhifeng Lin, Mehrdad Kiamari, Salman Avestimehr, Murali Annavaram:
Slack squeeze coded computing for adaptive straggler mitigation. SC 2019: 14:1-14:16 - [i6]Krishna Narra, Zhifeng Lin, Mehrdad Kiamari, Salman Avestimehr, Murali Annavaram:
Distributed Matrix Multiplication Using Speed Adaptive Coding. CoRR abs/1904.07098 (2019) - [i5]Krishna Giri Narra, Zhifeng Lin, Ganesh Ananthanarayanan, Salman Avestimehr, Murali Annavaram:
Collage Inference: Tolerating Stragglers in Distributed Neural Network Inference using Coding. CoRR abs/1904.12222 (2019) - [i4]Krishna Narra, Zhifeng Lin, Ganesh Ananthanarayanan, Salman Avestimehr, Murali Annavaram:
Collage Inference: Achieving low tail latency during distributed image classification using coded redundancy models. CoRR abs/1906.03999 (2019) - [i3]Zhifeng Lin, Krishna Giri Narra, Mingchao Yu, Salman Avestimehr, Murali Annavaram:
Train Where the Data is: A Case for Bandwidth Efficient Coded Training. CoRR abs/1910.10283 (2019) - [i2]Krishna Giri Narra, Zhifeng Lin, Yongqin Wang, Keshav Balasubramaniam, Murali Annavaram:
Privacy-Preserving Inference in Machine Learning Services Using Trusted Execution Environments. CoRR abs/1912.03485 (2019) - 2018
- [c2]Mingchao Yu, Zhifeng Lin, Krishna Narra, Songze Li, Youjie Li, Nam Sung Kim, Alexander G. Schwing, Murali Annavaram, Salman Avestimehr:
GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training. NeurIPS 2018: 5129-5139 - [i1]Mingchao Yu, Zhifeng Lin, Krishna Narra, Songze Li, Youjie Li, Nam Sung Kim, Alexander G. Schwing, Murali Annavaram, Salman Avestimehr:
GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training. CoRR abs/1811.03617 (2018) - 2017
- [c1]Gunjae Koo, Kiran Kumar Matam, Te I, H. V. Krishna Giri Narra, Jing Li, Hung-Wei Tseng, Steven Swanson, Murali Annavaram:
Summarizer: trading communication with computing near storage. MICRO 2017: 219-231
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