• Multiple source replacement path problem 

  Gupta, Manoj; Jain, Rahul; Modi, Nitiksha (03-08-20)
• Efficient hierarchical clustering for classification and anomaly detection 

  Doshi, Ishita; Sajjalla, Sreekalyan; Choudhari, Jayesh; Bhatt, Rushi; Dasgupta, Anirban (Cornell University Library, 2020-08)

  We address the problem of large scale real time classification of content posted on social networks, along with the need to rapidly identify novel spam types. Obtaining manual labels for user generated content using editorial ...
• Spatial sharing of GPU for autotuning DNN models 

  Dhakal, Aditya; Cho, Junguk; Kulkarni, Sameer G.; Ramakrishnan, K. K.; Sharma, Puneet (Cornell University Library, 2020-08)

  GPUs are used for training, inference, and tuning the machine learning models. However, Deep Neural Network (DNN) vary widely in their ability to exploit the full power of high-performance GPUs. Spatial sharing of GPU ...
• Gandhipedia: a one-stop AI-enabled portal for browsing Gandhian literature, life-events and his social network 

  Adak, Sayantan; Vyas, Atharva; Mukherjee, Animesh; Ambavi, Heer; Kadasi, Pritam; Singh, Mayank; Patel, Shivam (2020-08-01)
• Understanding consumer preferences for movie trailers from EEG using machine learning 

  Pandey, Pankaj; Swarnkar, Raunak; Kakaria, Shobhit; Miyapuram, Krishna Prasad (2019-12-10)
• PredCheck: detecting predatory behaviour in scholarly world 

  Bedmutha, Manas Satish; Modi, Kaushal; Patel, Kevin; Jain, Naman; Singh, Mayank (2020-08-01)
• Identification, tracking and impact: understanding the trade secret of catchphrases 

  Jalal, Jagriti; Singh, Mayank; Pal, Arindam; Dey, Lipika; Mukherjee, Animesh (2020-08-01)
• SEAL: Scientific keyphrase extraction and classification 

  Garg, Ayush; Kagi, Sammed Shantinath; Singh, Mayank (2020-08-01)
• A multistep priority-based ranking for top-N recommendation using social and tag information 

  Banerjee, Suman; Banjare, Pratik; Pal, Bithika; Jenamani, Mamata (Springer, 2020-08)

  Recommender system is a collection of information retrieval tools and techniques used for recommending items to users based on their choices. For improving recommendation accuracy, the use of extra information (e.g., social, ...
• Bollyrics: automatic lyrics generator for Romanised Hindi 

  Jain, Naman; Chauhan, Ankush; Chewale, Atharva; Mithbavkar, Ojas; Shah, Ujjaval; Singh, Mayank (Cornell University Library, 2020-07)
• Understanding container network interface plugins: design considerations and performance 

  Qi, Shixiong; Kulkarni, Sameer G.; Ramakrishnan, K. K. (2020-07-13)
• Managing state for failure resiliency in network function virtualization 

  Kulkarni, Sameer G.; Ramakrishnan, K. K.; Wood, Timothy (2020-07-13)
• Active learning for air quality station deployment 

  Narayanan, S. Deepak; Agnihotri, Apoorv; Batra, Nipun (2020-07-17)
• Identification, tracking and impact: understanding the trade secret of catchphrases 

  Jalal, Jagriti; Singh, Mayank; Pal, Arindam; Dey, Lipika; Mukherjee, Animesh (Cornell University Library, 2020-07)
• Scalable estimation of epidemic thresholds via node sampling 

  Dasgupta, Anirban; Sengupta, Srijan (Cornell University Library, 2020-07)

  Infectious or contagious diseases can be transmitted from one person to another through social contact networks. In today's interconnected global society, such contagion processes can cause global public health hazards, ...
• Depthwise spatio-temporal STFT convolutional neural networks for human action recognition 

  Kumawat, Sudhakar; Verma, Manisha; Nakashima, Yuta; Raman, Shanmuganathan (Cornell University Library, 2020-07)

  Conventional 3D convolutional neural networks (CNNs) are computationally expensive, memory intensive, prone to overfitting, and most importantly, there is a need to improve their feature learning capabilities. To address ...
• Understanding consumer preferences for movie trailers from EEG using machine learning 

  Pandey, Pankaj; Swarnkar, Raunak; Kakaria, Shobhit; Miyapuram, Krishna Prasad (Cornell University Library, 2020-07)

  Neuromarketing aims to understand consumer behavior using neuroscience. Brain imaging tools such as EEG have been used to better understand consumer behavior that goes beyond self-report measures which can be a more accurate ...
• An efficient updation approach for enumerating maximal (?, ?)-cliques of a temporal network 

  Banerjee, Suman; Pal, Bithika (Cornell University Library, 2020-07)
• IIT Gandhinagar at SemEval-2020 task 9: code-mixed sentiment classification using candidate sentence generation and selection 

  Srivastava, Vivek; Singh, Mayank (Cornell University Library, 2020-06)
• Prefetching in hybrid main memory systems 

  V., Subisha; Gohil, Varun; Ujjainkar, Nisarg; Awasthi, Manu (2020-07-13)

View more