Dynamical feature extraction at the sensory periphery guides chemotaxis von Schulze, Aljoscha, Gomez-Marin, Alex, Rajendran, Vani G, Lott, Gus, Musy, Marco, Ahammad, Parvez, Deogade, Ajinkya, Sharpe, James, Riedl, Julia, Jarriault, David, Trautman, Eric T, Werner, Christopher, Venkadesan, Madhusudhan, Druckmann, Shaul, Jayaraman, Vivek, Louis, Matthieu

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MCA-Based Rule Mining Enables Interpretable Inference in Clinical Psychiatry von Gao, Qingzhu, Gonzalez, Humberto, Ahammad, Parvez

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Unsupervised segmentation of noisy electron microscopy images using salient watersheds and region merging von Navlakha, Saket, Ahammad, Parvez, Myers, Eugene W

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Automated Reconstruction of Neuronal Morphology Based on Local Geometrical and Global Structural Models von Zhao, Ting, Xie, Jun, Amat, Fernando, Clack, Nathan, Ahammad, Parvez, Peng, Hanchuan, Long, Fuhui, Myers, Eugene

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LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale von Rogers, Ryan, Subramaniam, Subbu, Peng, Sean, Durfee, David, Lee, Seunghyun, Kancha, Santosh Kumar, Sahay, Shraddha, Ahammad, Parvez

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Coding of Image Feature Descriptors for Distributed Rate-efficient Visual Correspondences von Yeo, Chuohao, Ahammad, Parvez, Ramchandran, Kannan

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Machine Learning Models Identify Multimodal Measurements Highly Predictive of Transdiagnostic Symptom Severity for Mood, Anhedonia, and Anxiety von Mellem, Monika S., Liu, Yuelu, Gonzalez, Humberto, Kollada, Matthew, Martin, William J., Ahammad, Parvez

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High-Speed Action Recognition and Localization in Compressed Domain Videos von Chuohao Yeo, Ahammad, P., Ramchandran, K., Sastry, S.S.

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LinkedIn's Audience Engagements API von Ryan Rogers, Subbu Subramaniam, Sean Peng, David Durfee, Seunghyun Lee, Santosh Kumar Kancha, Shraddha Sahay, Parvez Ahammad

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Machine Learning Identifies Large-Scale Reward-Related Activity Modulated by Dopaminergic Enhancement in Major Depression von Liu, Yuelu, Admon, Roee, Mellem, Monika S., Belleau, Emily L., Kaiser, Roselinde H., Clegg, Rachel, Beltzer, Miranda, Goer, Franziska, Vitaliano, Gordana, Ahammad, Parvez, Pizzagalli, Diego A.

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A Low-Bandwidth Camera Sensor Platform with Applications in Smart Camera Networks von CHEN, Phoebus, HONG, Kirak, LOBATON, Edgar, OH, Songhwai, AHAMMAD, Parvez, NAIKAL, Nikhil, SASTRY, S. Shankar, TYGAR, Doug, YAN, Posu, YANG, Allen Y, CHANG, Lung-Chung, LIN, Leon, WANG, Simon

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Rate-efficient visual correspondences using random projections von Chuohao Yeo, Ahammad, P., Ramchandran, K.

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Dynamical feature extraction at the sensory periphery guides chemotaxis von Schulze, Aljoscha, 1980, Gómez Marín, Alex, Rajendran, Vani G, Lott, Gus, Musy, Marco, Ahammad, Parvez, Deogade, Ajinkya, 1989, Sharpe, James, Riedl, Julia, 1981, Jarriault, David, Trautman, Eric T, Werner, Christopher, Venkadesan, Madhusudhan, Druckmann, Shaul, Jayaraman, Vivek, Louis, Matthieu

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Dynamical feature extraction at the sensory periphery guides chemotaxis von Schulze, Aljoscha, 1980, Gómez Marín, Alex, Rajendran, Vani G, Lott, Gus, Musy, Marco, Ahammad, Parvez, Deogade, Ajinkya, Sharpe, James, Riedl, Julia, 1981, Jarriault, David, Trautman, Eric T, Werner, Christopher, Venkadesan, Madhusudhan, Druckmann, Shaul, Jayaraman, Vivek, Louis, Matthieu

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High-Speed Action Recognition and Localization in Compressed Domain Videos: Video Surveillance von YEO, Chuohao, AHAMMAD, Parvez, RAMCHANDRAN, Kannan, SHANKAR SASTRY, S

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CrystalCandle: A User-Facing Model Explainer for Narrative Explanations von Yang, Jilei, Negoescu, Diana, Ahammad, Parvez

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Fast, real-time, estimation of content-sensitive encoding quality for optimized web delivery of images von Ahammad, Parvez

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Sales Channel Optimization via Simulations Based on Observational Data with Delayed Rewards: A Case Study at LinkedIn von Negoescu, Diana M, Khosravi, Pasha, Zhao, Shadow, Chen, Nanyu, Ahammad, Parvez, Gonzalez, Humberto

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Recommending and prioritizing computer log anomalies von Jiang, Heju, Ahammad, Parvez

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MCA-based Rule Mining Enables Interpretable Inference in Clinical Psychiatry von Gao, Qingzhu, Gonzalez, Humberto, Ahammad, Parvez

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