• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 48 matches

• 2024
• 
  Matthew Jagielski, Om Thakkar, Lun Wang:
  Noise Masking Attacks and Defenses for Pretrained Speech Models. ICASSP 2024: 4810-4814
• 
  Lun Wang, Om Thakkar, Rajiv Mathews:
  Unintended Memorization in Large ASR Models, and How to Mitigate It. ICASSP 2024: 4655-4659
• 
  Omer Dunay, Daniel Cheng, Adam Tait, Parth Thakkar, Peter C. Rigby, Andy Chiu, Imad Ahmad, Arun Ganesan, Chandra Shekhar Maddila, Vijayaraghavan Murali, Ali Tayyebi, Nachiappan Nagappan:
  Multi-line AI-Assisted Code Authoring. SIGSOFT FSE Companion 2024: 150-160
• 
  Omer Dunay, Daniel Cheng, Adam Tait, Parth Thakkar, Peter C. Rigby, Andy Chiu, Imad Ahmad, Arun Ganesan, Chandra Shekhar Maddila, Vijayaraghavan Murali, Ali Tayyebi, Nachiappan Nagappan:
  Multi-line AI-assisted Code Authoring. CoRR abs/2402.04141 (2024)
• 
  Matthew Jagielski, Om Thakkar, Lun Wang:
  Noise Masking Attacks and Defenses for Pretrained Speech Models. CoRR abs/2404.02052 (2024)
• 
  Lun Wang, Om Thakkar, Zhong Meng, Nicole Rafidi, Rohit Prabhavalkar, Arun Narayanan:
  Efficiently Train ASR Models that Memorize Less and Perform Better with Per-core Clipping. CoRR abs/2406.02004 (2024)
• 2023
• 
  Neha Sisodiya, Nitant Dube, Om Prakash, Priyank Thakkar:
  Scalable big earth observation data mining algorithms: a review. Earth Sci. Informatics 16(3): 1993-2016 (2023)
• 
  Matthew Jagielski, Om Thakkar, Florian Tramèr, Daphne Ippolito, Katherine Lee, Nicholas Carlini, Eric Wallace, Shuang Song, Abhradeep Guha Thakurta, Nicolas Papernot, Chiyuan Zhang:
  Measuring Forgetting of Memorized Training Examples. ICLR 2023
• 
  Arun Ganesh, Mahdi Haghifam, Milad Nasr, Sewoong Oh, Thomas Steinke, Om Thakkar, Abhradeep Guha Thakurta, Lun Wang:
  Why Is Public Pretraining Necessary for Private Model Training? ICML 2023: 10611-10627
• 
  Arun Ganesh, Mahdi Haghifam, Milad Nasr, Sewoong Oh, Thomas Steinke, Om Thakkar, Abhradeep Thakurta, Lun Wang:
  Why Is Public Pretraining Necessary for Private Model Training? CoRR abs/2302.09483 (2023)
• 
  Lun Wang, Om Thakkar, Rajiv Mathews:
  Unintended Memorization in Large ASR Models, and How to Mitigate It. CoRR abs/2310.11739 (2023)
• 2022
• 
  Shubhankar Mohapatra, Sajin Sasy, Xi He, Gautam Kamath, Om Thakkar:
  The Role of Adaptive Optimizers for Honest Private Hyperparameter Selection. AAAI 2022: 7806-7813
• 
  Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays:
  A Method to Reveal Speaker Identity in Distributed ASR Training, and How to Counter IT. ICASSP 2022: 4338-4342
• 
  Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta:
  Public Data-Assisted Mirror Descent for Private Model Training. ICML 2022: 517-535
• 
  Ehsan Amid, Om Dipakbhai Thakkar, Arun Narayanan, Rajiv Mathews, Françoise Beaufays:
  Extracting Targeted Training Data from ASR Models, and How to Mitigate It. INTERSPEECH 2022: 2803-2807
• 
  W. Ronny Huang, Steve Chien, Om Dipakbhai Thakkar, Rajiv Mathews:
  Detecting Unintended Memorization in Language-Model-Fused ASR. INTERSPEECH 2022: 2808-2812
• 
  Ehsan Amid, Om Thakkar, Arun Narayanan, Rajiv Mathews, Françoise Beaufays:
  Extracting Targeted Training Data from ASR Models, and How to Mitigate It. CoRR abs/2204.08345 (2022)
• 
  W. Ronny Huang, Steve Chien, Om Thakkar, Rajiv Mathews:
  Detecting Unintended Memorization in Language-Model-Fused ASR. CoRR abs/2204.09606 (2022)
• 
  Matthew Jagielski, Om Thakkar, Florian Tramèr, Daphne Ippolito, Katherine Lee, Nicholas Carlini, Eric Wallace, Shuang Song, Abhradeep Thakurta, Nicolas Papernot, Chiyuan Zhang:
  Measuring Forgetting of Memorized Training Examples. CoRR abs/2207.00099 (2022)
• 
  Virat Shejwalkar, Arun Ganesh, Rajiv Mathews, Om Thakkar, Abhradeep Thakurta:
  Recycling Scraps: Improving Private Learning by Leveraging Intermediate Checkpoints. CoRR abs/2210.01864 (2022)
• 2021
• 
  Shuang Song, Thomas Steinke, Om Thakkar, Abhradeep Thakurta:
  Evading the Curse of Dimensionality in Unconstrained Private GLMs. AISTATS 2021: 2638-2646
• 
  Peter Kairouz, Brendan McMahan, Shuang Song, Om Thakkar, Abhradeep Thakurta, Zheng Xu:
  Practical and Private (Deep) Learning Without Sampling or Shuffling. ICML 2021: 5213-5225
• 
  Galen Andrew, Om Thakkar, Brendan McMahan, Swaroop Ramaswamy:
  Differentially Private Learning with Adaptive Clipping. NeurIPS 2021: 17455-17466
• 
  Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays:
  Revealing and Protecting Labels in Distributed Training. NeurIPS 2021: 1727-1738
• 
  Peter Kairouz, Brendan McMahan, Shuang Song, Om Thakkar, Abhradeep Thakurta, Zheng Xu:
  Practical and Private (Deep) Learning without Sampling or Shuffling. CoRR abs/2103.00039 (2021)
• 
  Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays:
  A Method to Reveal Speaker Identity in Distributed ASR Training, and How to Counter It. CoRR abs/2104.07815 (2021)
• 
  Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays:
  Revealing and Protecting Labels in Distributed Training. CoRR abs/2111.00556 (2021)
• 
  Shubhankar Mohapatra, Sajin Sasy, Xi He, Gautam Kamath, Om Thakkar:
  The Role of Adaptive Optimizers for Honest Private Hyperparameter Selection. CoRR abs/2111.04906 (2021)
• 
  Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta:
  Public Data-Assisted Mirror Descent for Private Model Training. CoRR abs/2112.00193 (2021)
• 2020
• 
  Ryan Rogers, Aaron Roth, Adam D. Smith, Nathan Srebro, Om Thakkar, Blake E. Woodworth:
  Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis. AISTATS 2020: 2830-2840

skipping 18 more matches