Summarizer: trading communication with computing near storage. - Gunjae Koo; Kiran Kumar Matam; Te I; H. V. Krishna Giri Narra; Jing Li 021; Hung-Wei Tseng 001; Steven Swanson; Murali Annavaram (MICRO, 2017)

GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training. - Mingchao Yu; Zhifeng Lin; Krishna Narra; Songze Li; Youjie Li; Nam Sung Kim; Alexander G. Schwing; Murali Annavaram; Salman Avestimehr (NeurIPS, 2018)

Slack squeeze coded computing for adaptive straggler mitigation. - Krishna Giri Narra; Zhifeng Lin; Mehrdad Kiamari; Salman Avestimehr; Murali Annavaram (SC, 2019)

Distributed Matrix Multiplication Using Speed Adaptive Coding. - Krishna Narra; Zhifeng Lin; Mehrdad Kiamari; Salman Avestimehr; Murali Annavaram (CoRR, 2019)

Collage Inference: Tolerating Stragglers in Distributed Neural Network Inference using Coding. - Krishna Giri Narra; Zhifeng Lin; Ganesh Ananthanarayanan; Salman Avestimehr; Murali Annavaram (CoRR, 2019)

Collage Inference: Achieving low tail latency during distributed image classification using coded redundancy models. - Krishna Narra; Zhifeng Lin; Ganesh Ananthanarayanan; Salman Avestimehr; Murali Annavaram (CoRR, 2019)

Train Where the Data is: A Case for Bandwidth Efficient Coded Training. - Zhifeng Lin; Krishna Giri Narra; Mingchao Yu; Salman Avestimehr; Murali Annavaram (CoRR, 2019)

Privacy-Preserving Inference in Machine Learning Services Using Trusted Execution Environments. - Krishna Giri Narra; Zhifeng Lin; Yongqin Wang; Keshav Balasubramaniam; Murali Annavaram (CoRR, 2019)

Collage Inference: Using Coded Redundancy for Lowering Latency Variation in Distributed Image Classification Systems. - Hema Venkata Krishna Giri Narra; Zhifeng Lin; Ganesh Ananthanarayanan; Salman Avestimehr; Murali Annavaram (ICDCS, 2020)

Origami Inference: Private Inference Using Hardware Enclaves. - Krishna Giri Narra; Zhifeng Lin; Yongqin Wang; Keshav Balasubramanian; Murali Annavaram (CLOUD, 2021)

Private Ad Modeling with DP-SGD. - Carson Denison; Badih Ghazi; Pritish Kamath; Ravi Kumar 001; Pasin Manurangsi; Krishna Giri Narra; Amer Sinha; Avinash V. Varadarajan; Chiyuan Zhang (AdKDD@KDD, 2023)

Training Differentially Private Ad Prediction Models With Semi-Sensitive Features. - Lynn Chua; Qiliang Cui; Badih Ghazi; Charlie Harrison; Pritish Kamath; Walid Krichene; Ravi Kumar 001; Pasin Manurangsi; Nicolas Mayoraz; Hema Venkata Krishna Giri Narra; Steffen Rendle; Amer Sinha; et al. (AdKDD@KDD, 2024)

Training Differentially Private Ad Prediction Models with Semi-Sensitive Features. - Lynn Chua; Qiliang Cui; Badih Ghazi; Charlie Harrison; Pritish Kamath; Walid Krichene; Ravi Kumar 001; Pasin Manurangsi; Krishna Giri Narra; Amer Sinha; Avinash V. Varadarajan; Chiyuan Zhang (CoRR, 2024)