David D. Cox - RankMe

106 papers A* 19A 4B 2C 3Misc 2Journal 58Unranked 18

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	LLMON: An LLM-native Markup Language to Leverage Structure and Semantics at the LLM Interface. CoRR Michael Hind, Basel Shbita, Bo Wu, Farhan Ahmed, Chad DeLuca, Nathan Fulton, David D. Cox, Dan Gutfreund
2025	J	`jnl`	A Scalable NorthPole System with End-to-End Vertical Integration for Low-Latency and Energy-Efficient LLM Inference. CoRR Michael V. DeBole, Rathinakumar Appuswamy, Neil McGlohon, Brian Taba, Steven K. Esser, Filipp Akopyan, John V. Arthur, Arnon Amir, Alexander Andreopoulos, Peter J. Carlson, Andrew S. Cassidy, Pallab Datta, Myron D. Flickner, Rajamohan Gandhasri, Guillaume J. Garreau, Megumi Ito, Jennifer L. Klamo, Jeffrey A. Kusnitz, Nathaniel J. McClatchey, Jeffrey L. McKinstry, Tapan K. Nayak, Carlos Ortega Otero, Hartmut Penner, William P. Risk, Jun Sawada, Jay Sivagnaname, Daniel F. Smith, Rafael Sousa, Ignacio Terrizzano, Takanori Ueda, Trent Gray-Donald, David D. Cox, Dharmendra S. Modha
2025	J	`jnl`	A System for Accurate Tracking and Video Recordings of Rodent Eye Movements using Convolutional Neural Networks for Biomedical Image Segmentation. CoRR Isha Puri, David D. Cox
2025	J	`jnl`	Granite Vision: a lightweight, open-source multimodal model for enterprise Intelligence. CoRR Leonid Karlinsky, Assaf Arbelle, Abraham Daniels, Ahmed Nassar, Amit Alfassi, Bo Wu, Eli Schwartz, Dhiraj Joshi, Jovana Kondic, Nimrod Shabtay, Pengyuan Li, Roei Herzig, Shafiq Abedin, Shaked Perek, Sivan Harary, Udi Barzelay, Adi Raz Goldfarb, Aude Oliva, Ben Wieles, Bishwaranjan Bhattacharjee, Brandon Huang, Christoph Auer, Dan Gutfreund, David Beymer, David Wood, Hilde Kuehne, Jacob A. Hansen, Joseph Shtok, Ken Wong, Luis Angel D. Bathen, Mayank Mishra, Maksym Lysak, Michele Dolfi, Mikhail Yurochkin, Nikolaos Livathinos, Nimrod Harel, Ophir Azulai, Oshri Naparstek, Rafael Teixeira de Lima, Rameswar Panda, Sivan Doveh, Shubham Gupta, Subhro Das, Syed Zawad, Yusik Kim, Zexue He, Alexander Brooks, Gabe Goodhart, Anita Govindjee, Derek Leist, Ibrahim Ibrahim, Aya Soffer, David D. Cox, Kate Soule, Luis A. Lastras, Nirmit Desai, Shila Ofek-Koifman, Sriram Raghavan, Tanveer F. Syeda-Mahmood, Peter W. J. Staar, Tal Drory, Rogério Feris
2024	—	`conf`	Breakthrough Low-Latency, High-Energy-Efficiency LLM Inference Performance Using NorthPole. HPEC Rathinakumar Appuswamy, Michael V. DeBole, Brian Taba, Steven K. Esser, Andrew S. Cassidy, Arnon Amir, Alexander Andreopoulos, Deepika Bablani, Pallab Datta, Jeffrey A. Kusnitz, Nathaniel J. McClatchey, Neil McGlohon, Jeffrey L. McKinstry, Tapan K. Nayak, Daniel F. Smith, Rafael Sousa, Ignacio Terrizzano, Filipp Akopyan, Peter J. Carlson, Rajamohan Gandhasri, Guillaume Garreau, Nelson M. Gonzalez, Megumi Ito, Jennifer L. Klamo, Yutaka Y. Nakamura, Carlos Ortega Otero, William P. Risk, Jun Sawada, Kai Schleupen, Jay Sivagnaname, Matthew Stallone, Takanori Ueda, Myron D. Flickner, John V. Arthur, Rameswar Panda, David D. Cox, Dharmendra S. Modha
2024	J	`jnl`	Granite Code Models: A Family of Open Foundation Models for Code Intelligence. CoRR Mayank Mishra, Matt Stallone, Gaoyuan Zhang, Yikang Shen, Aditya Prasad, Adriana Meza Soria, Michele Merler, Parameswaran Selvam, Saptha Surendran, Shivdeep Singh, Manish Sethi, Xuan-Hong Dang, Pengyuan Li, Kun-Lung Wu, Syed Zawad, Andrew Coleman, Matthew White, Mark Lewis, Raju Pavuluri, Yan Koyfman, Boris Lublinsky, Maximilien de Bayser, Ibrahim Abdelaziz, Kinjal Basu, Mayank Agarwal, Yi Zhou, Chris Johnson, Aanchal Goyal, Hima Patel, Syed Yousaf Shah, Petros Zerfos, Heiko Ludwig, Asim Munawar, Maxwell Crouse, Pavan Kapanipathi, Shweta Salaria, Bob Calio, Sophia Wen, Seetharami Seelam, Brian Belgodere, Carlos A. Fonseca, Amith Singhee, Nirmit Desai, David D. Cox, Ruchir Puri, Rameswar Panda
2024	J	`jnl`	LAB: Large-Scale Alignment for ChatBots. CoRR Shivchander Sudalairaj, Abhishek Bhandwaldar, Aldo Pareja, Kai Xu, David D. Cox, Akash Srivastava
2024	J	`jnl`	Power Scheduler: A Batch Size and Token Number Agnostic Learning Rate Scheduler. CoRR Yikang Shen, Matthew Stallone, Mayank Mishra, Gaoyuan Zhang, Shawn Tan, Aditya Prasad, Adriana Meza Soria, David D. Cox, Rameswar Panda
2024	J	`jnl`	Scaling Granite Code Models to 128K Context. CoRR Matt Stallone, Vaibhav Saxena, Leonid Karlinsky, Bridget McGinn, Tim Bula, Mayank Mishra, Adriana Meza Soria, Gaoyuan Zhang, Aditya Prasad, Yikang Shen, Saptha Surendran, Shanmukha C. Guttula, Hima Patel, Parameswaran Selvam, Xuan-Hong Dang, Yan Koyfman, Atin Sood, Rogério Feris, Nirmit Desai, David D. Cox, Ruchir Puri, Rameswar Panda
2024	J	`jnl`	Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts. CoRR Junmo Kang, Leonid Karlinsky, Hongyin Luo, Zhen Wang, Jacob A. Hansen, Jim Glass, David D. Cox, Rameswar Panda, Rogério Feris, Alan Ritter
2024	—	`conf`	Self-Specialization: Uncovering Latent Expertise within Large Language Models. ACL (Findings) Junmo Kang, Hongyin Luo, Yada Zhu, Jacob A. Hansen, James R. Glass, David D. Cox, Alan Ritter, Rogério Feris, Leonid Karlinsky
2024	A*	`conf`	Trans-LoRA: towards data-free Transferable Parameter Efficient Finetuning. NeurIPS Runqian Wang, Soumya Ghosh, David D. Cox, Diego Antognini, Aude Oliva, Rogério Feris, Leonid Karlinsky
2024	J	`jnl`	Trans-LoRA: towards data-free Transferable Parameter Efficient Finetuning. CoRR Runqian Wang, Soumya Ghosh, David D. Cox, Diego Antognini, Aude Oliva, Rogério Feris, Leonid Karlinsky
2023	C	`conf`	Audio-Visual Neural Syntax Acquisition. ASRU Cheng-I Jeff Lai, Freda Shi, Puyuan Peng, Yoon Kim, Kevin Gimpel, Shiyu Chang, Yung-Sung Chuang, Saurabhchand Bhati, David D. Cox, David Harwath, Yang Zhang, Karen Livescu, James R. Glass
2023	J	`jnl`	Audio-Visual Neural Syntax Acquisition. CoRR Cheng-I Jeff Lai, Freda Shi, Puyuan Peng, Yoon Kim, Kevin Gimpel, Shiyu Chang, Yung-Sung Chuang, Saurabhchand Bhati, David D. Cox, David Harwath, Yang Zhang, Karen Livescu, James R. Glass
2023	A*	`conf`	ConStruct-VL: Data-Free Continual Structured VL Concepts Learning. CVPR James Seale Smith, Paola Cascante-Bonilla, Assaf Arbelle, Donghyun Kim, Rameswar Panda, David D. Cox, Diyi Yang, Zsolt Kira, Rogério Feris, Leonid Karlinsky
2023	A*	`conf`	Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision. NeurIPS Zhiqing Sun, Yikang Shen, Qinhong Zhou, Hongxin Zhang, Zhenfang Chen, David D. Cox, Yiming Yang, Chuang Gan
2023	J	`jnl`	Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision. CoRR Zhiqing Sun, Yikang Shen, Qinhong Zhou, Hongxin Zhang, Zhenfang Chen, David D. Cox, Yiming Yang, Chuang Gan
2023	J	`jnl`	SALMON: Self-Alignment with Principle-Following Reward Models. CoRR Zhiqing Sun, Yikang Shen, Hongxin Zhang, Qinhong Zhou, Zhenfang Chen, David D. Cox, Yiming Yang, Chuang Gan
2023	J	`jnl`	Self-Specialization: Uncovering Latent Expertise within Large Language Models. CoRR Junmo Kang, Hongyin Luo, Yada Zhu, James R. Glass, David D. Cox, Alan Ritter, Rogério Feris, Leonid Karlinsky
2022	A*	`conf`	An Adversarial Framework for Generating Unseen Images by Activation Maximization. AAAI Yang Zhang, Wang Zhou, Gaoyuan Zhang, David D. Cox, Shiyu Chang
2022	J	`jnl`	ConStruct-VL: Data-Free Continual Structured VL Concepts Learning. CoRR James Seale Smith, Paola Cascante-Bonilla, Assaf Arbelle, Donghyun Kim, Rameswar Panda, David D. Cox, Diyi Yang, Zsolt Kira, Rogério Feris, Leonid Karlinsky
2022	A*	`conf`	ContentVec: An Improved Self-Supervised Speech Representation by Disentangling Speakers. ICML Kaizhi Qian, Yang Zhang, Heting Gao, Junrui Ni, Cheng-I Lai, David D. Cox, Mark Hasegawa-Johnson, Shiyu Chang
2022	J	`jnl`	Improving Self-Supervised Speech Representations by Disentangling Speakers. CoRR Kaizhi Qian, Yang Zhang, Heting Gao, Junrui Ni, Cheng-I Lai, David D. Cox, Mark Hasegawa-Johnson, Shiyu Chang
2022	Misc	`conf`	On the Interplay between Sparsity, Naturalness, Intelligibility, and Prosody in Speech Synthesis. ICASSP Cheng-I Jeff Lai, Erica Cooper, Yang Zhang, Shiyu Chang, Kaizhi Qian, Yi-Lun Liao, Yung-Sung Chuang, Alexander H. Liu, Junichi Yamagishi, David D. Cox, James R. Glass
2022	A*	`conf`	VALHALLA: Visual Hallucination for Machine Translation. CVPR Yi Li, Rameswar Panda, Yoon Kim, Chun-Fu Richard Chen, Rogério Feris, David D. Cox, Nuno Vasconcelos
2022	J	`jnl`	VALHALLA: Visual Hallucination for Machine Translation. CoRR Yi Li, Rameswar Panda, Yoon Kim, Chun-Fu Chen, Rogério Feris, David D. Cox, Nuno Vasconcelos
2021	A*	`conf`	Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators. ICML Yonggan Fu, Yongan Zhang, Yang Zhang, David D. Cox, Yingyan Lin
2021	J	`jnl`	Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators. CoRR Yonggan Fu, Yongan Zhang, Yang Zhang, David D. Cox, Yingyan Lin
2021	A*	`conf`	Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks. NeurIPS Yonggan Fu, Qixuan Yu, Yang Zhang, Shang Wu, Xu Ouyang, David D. Cox, Yingyan Lin
2021	J	`jnl`	Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks. CoRR Yonggan Fu, Qixuan Yu, Yang Zhang, Shang Wu, Xu Ouyang, David D. Cox, Yingyan Lin
2021	A*	`conf`	Global Prosody Style Transfer Without Text Transcriptions. ICML Kaizhi Qian, Yang Zhang, Shiyu Chang, Jinjun Xiong, Chuang Gan, David D. Cox, Mark Hasegawa-Johnson
2021	J	`jnl`	Global Rhythm Style Transfer Without Text Transcriptions. CoRR Kaizhi Qian, Yang Zhang, Shiyu Chang, Jinjun Xiong, Chuang Gan, David D. Cox, Mark Hasegawa-Johnson
2021	A	`conf`	Joint Visual-Temporal Embedding for Unsupervised Learning of Actions in Untrimmed Sequences. WACV Rosaura G. VidalMata, Walter J. Scheirer, Anna Kukleva, David D. Cox, Hilde Kuehne
2021	J	`jnl`	Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks. Neural Comput. Germán Abrevaya, Guillaume Dumas, Aleksandr Y. Aravkin, Peng Zheng, Jean-Christophe Gagnon-Audet, James R. Kozloski, Pablo Polosecki, Guillaume Lajoie, David D. Cox, Silvina Ponce Dawson, Guillermo A. Cecchi, Irina Rish
2021	A*	`conf`	Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception. NeurIPS Joel Dapello, Jenelle Feather, Hang Le, Tiago Marques, David D. Cox, Josh H. McDermott, James J. DiCarlo, SueYeon Chung
2021	J	`jnl`	Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception. CoRR Joel Dapello, Jenelle Feather, Hang Le, Tiago Marques, David D. Cox, Josh H. McDermott, James J. DiCarlo, SueYeon Chung
2021	J	`jnl`	On the Interplay Between Sparsity, Naturalness, Intelligibility, and Prosody in Speech Synthesis. CoRR Cheng-I Jeff Lai, Erica Cooper, Yang Zhang, Shiyu Chang, Kaizhi Qian, Yi-Lun Liao, Yung-Sung Chuang, Alexander H. Liu, Junichi Yamagishi, David D. Cox, James R. Glass
2021	A*	`conf`	PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition. NeurIPS Cheng-I Jeff Lai, Yang Zhang, Alexander H. Liu, Shiyu Chang, Yi-Lun Liao, Yung-Sung Chuang, Kaizhi Qian, Sameer Khurana, David D. Cox, James R. Glass
2021	J	`jnl`	PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition. CoRR Cheng-I Jeff Lai, Yang Zhang, Alexander H. Liu, Shiyu Chang, Yi-Lun Liao, Yung-Sung Chuang, Kaizhi Qian, Sameer Khurana, David D. Cox, James R. Glass
2021	—	`conf`	ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation. NeurIPS Datasets and Benchmarks Chuang Gan, Jeremy Schwartz, Seth Alter, Damian Mrowca, Martin Schrimpf, James Traer, Julian De Freitas, Jonas Kubilius, Abhishek Bhandwaldar, Nick Haber, Megumi Sano, Kuno Kim, Elias Wang, Michael Lingelbach, Aidan Curtis, Kevin T. Feigelis, Daniel Bear, Dan Gutfreund, David D. Cox, Antonio Torralba, James J. DiCarlo, Josh Tenenbaum, Josh H. McDermott, Dan Yamins
2020	J	`jnl`	A neural network trained for prediction mimics diverse features of biological neurons and perception. Nat. Mach. Intell. William Lotter, Gabriel Kreiman, David D. Cox
2020	J	`jnl`	Experiences and Insights for Collaborative Industry-Academic Research in Artificial Intelligence. AI Mag. Lisa Amini, Ching-Hua Chen, David D. Cox, Aude Oliva, Antonio Torralba
2020	J	`jnl`	Improving the Reconstruction of Disentangled Representation Learners via Multi-Stage Modelling. CoRR Akash Srivastava, Yamini Bansal, Yukun Ding, Cole L. Hurwitz, Kai Xu, Bernhard Egger, Prasanna Sattigeri, Josh Tenenbaum, David D. Cox, Dan Gutfreund
2020	J	`jnl`	Lifelong Object Detection. CoRR Wang Zhou, Shiyu Chang, Norma E. Sosa, Hendrik F. Hamann, David D. Cox
2020	J	`jnl`	Object-Centric Diagnosis of Visual Reasoning. CoRR Jianwei Yang, Jiayuan Mao, Jiajun Wu, Devi Parikh, David D. Cox, Joshua B. Tenenbaum, Chuang Gan
2020	A*	`conf`	Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations. NeurIPS Joel Dapello, Tiago Marques, Martin Schrimpf, Franziska Geiger, David D. Cox, James J. DiCarlo
2020	J	`jnl`	ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation. CoRR Chuang Gan, Jeremy Schwartz, Seth Alter, Martin Schrimpf, James Traer, Julian De Freitas, Jonas Kubilius, Abhishek Bhandwaldar, Nick Haber, Megumi Sano, Kuno Kim, Elias Wang, Damian Mrowca, Michael Lingelbach, Aidan Curtis, Kevin T. Feigelis, Daniel M. Bear, Dan Gutfreund, David D. Cox, James J. DiCarlo, Josh H. McDermott, Joshua B. Tenenbaum, Daniel L. K. Yamins
2020	A*	`conf`	Unsupervised Speech Decomposition via Triple Information Bottleneck. ICML Kaizhi Qian, Yang Zhang, Shiyu Chang, Mark Hasegawa-Johnson, David D. Cox
2020	J	`jnl`	Unsupervised Speech Decomposition via Triple Information Bottleneck. CoRR Kaizhi Qian, Yang Zhang, Shiyu Chang, David D. Cox, Mark Hasegawa-Johnson
2020	J	`jnl`	not-so-BigGAN: Generating High-Fidelity Images on a Small Compute Budget. CoRR Seungwook Han, Akash Srivastava, Cole L. Hurwitz, Prasanna Sattigeri, David D. Cox
2019	A*	`conf`	More Is Less: Learning Efficient Video Representations by Big-Little Network and Depthwise Temporal Aggregation. NeurIPS Quanfu Fan, Chun-Fu (Richard) Chen, Hilde Kuehne, Marco Pistoia, David D. Cox
2019	J	`jnl`	More Is Less: Learning Efficient Video Representations by Big-Little Network and Depthwise Temporal Aggregation. CoRR Quanfu Fan, Chun-Fu Chen, Hilde Kuehne, Marco Pistoia, David D. Cox
2019	A*	`conf`	Self-Supervised Moving Vehicle Tracking With Stereo Sound. ICCV Chuang Gan, Hang Zhao, Peihao Chen, David D. Cox, Antonio Torralba
2019	J	`jnl`	Self-supervised Moving Vehicle Tracking with Stereo Sound. CoRR Chuang Gan, Hang Zhao, Peihao Chen, David D. Cox, Antonio Torralba
2019	J	`jnl`	SimVAE: Simulator-Assisted Training forInterpretable Generative Models. CoRR Akash Srivastava, Jessie C. Rosenberg, Dan Gutfreund, David D. Cox
2019	—	`conf`	Triton: an intermediate language and compiler for tiled neural network computations. MAPL@PLDI Philippe Tillet, Hsiang-Tsung Kung, David D. Cox
2019	A*	`conf`	ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization. NeurIPS Xiangyi Chen, Sijia Liu, Kaidi Xu, Xingguo Li, Xue Lin, Mingyi Hong, David D. Cox
2019	J	`jnl`	ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization. CoRR Xiangyi Chen, Sijia Liu, Kaidi Xu, Xingguo Li, Xue Lin, Mingyi Hong, David D. Cox
2018	—	`conf`	A System for Accurate Tracking and Video Recordings of Rodent Eye Movements using Convolutional Neural Networks for Biomedical Image Segmentation. EMBC Isha Puri, David D. Cox
2018	J	`jnl`	A neural network trained to predict future video frames mimics critical properties of biological neuronal responses and perception. CoRR William Lotter, Gabriel Kreiman, David D. Cox
2018	—	`conf`	Conditional Infilling GANs for Data Augmentation in Mammogram Classification. RAMBO+BIA+TIA@MICCAI Eric Wu, Kevin Wu, David D. Cox, William Lotter
2018	J	`jnl`	Conditional Infilling GANs for Data Augmentation in Mammogram Classification. CoRR Eric Wu, Kevin Wu, David D. Cox, William Lotter
2018	J	`jnl`	Input-Aware Auto-Tuning of Compute-Bound HPC Kernels. CoRR Philippe Tillet, David D. Cox
2018	J	`jnl`	Minnorm training: an algorithm for training over-parameterized deep neural networks. CoRR Yamini Bansal, Madhu Advani, David D. Cox, Andrew M. Saxe
2018	—	`conf`	On the Information Bottleneck Theory of Deep Learning. ICLR (Poster) Andrew M. Saxe, Yamini Bansal, Joel Dapello, Madhu Advani, Artemy Kolchinsky, Brendan D. Tracey, David D. Cox
2017	J	`jnl`	A Multi-Scale CNN and Curriculum Learning Strategy for Mammogram Classification. CoRR William Lotter, Greg Sorensen, David D. Cox
2017	—	`conf`	A Multi-scale CNN and Curriculum Learning Strategy for Mammogram Classification. DLMIA/ML-CDS@MICCAI William Lotter, Greg Sorensen, David D. Cox
2017	—	`conf`	Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning. ICLR (Poster) William Lotter, Gabriel Kreiman, David D. Cox
2017	Misc	`conf`	Infomax-ICA using Hessian-free optimization. ICASSP Philippe Tillet, H. T. Kung, David D. Cox
2017	A	`conf`	Input-aware auto-tuning of compute-bound HPC kernels. SC Philippe Tillet, David D. Cox
2017	J	`jnl`	Recurrent computations for visual pattern completion. CoRR Hanlin Tang, Bill Lotter, Martin Schrimpf, Ana Paredes, Josue Ortega Caro, Walter Hardesty, David D. Cox, Gabriel Kreiman
2017	J	`jnl`	Using Human Brain Activity to Guide Machine Learning. CoRR Ruth Fong, Walter J. Scheirer, David D. Cox
2016	J	`jnl`	Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning. CoRR William Lotter, Gabriel Kreiman, David D. Cox
2016	—	`conf`	Tensor Switching Networks. NIPS Chuan-Yung Tsai, Andrew M. Saxe, David D. Cox
2016	J	`jnl`	Tensor Switching Networks. CoRR Chuan-Yung Tsai, Andrew M. Saxe, David D. Cox
2016	J	`jnl`	Visual Place Recognition: A Survey. IEEE Trans. Robotics Stephanie M. Lowry, Niko Sünderhauf, Paul Newman, John J. Leonard, David D. Cox, Peter I. Corke, Michael J. Milford
2015	C	`conf`	Fine-Tuning Convolutional Neural Networks Using Harmony Search. CIARP Gustavo H. Rosa, João Paulo Papa, Aparecido Nilceu Marana, Walter J. Scheirer, David D. Cox
2015	C	`conf`	Improving Optimum-Path Forest Classification Using Confidence Measures. CIARP Silas Evandro Nachif Fernandes, Walter J. Scheirer, David D. Cox, João Paulo Papa
2015	J	`jnl`	Measuring and Understanding Sensory Representations within Deep Networks Using a Numerical Optimization Framework. CoRR Chuan-Yung Tsai, David D. Cox
2015	J	`jnl`	Model selection for Discriminative Restricted Boltzmann Machines through meta-heuristic techniques. J. Comput. Sci. João Paulo Papa, Gustavo H. Rosa, Aparecido Nilceu Marana, Walter J. Scheirer, David D. Cox
2015	J	`jnl`	Unsupervised Learning of Visual Structure using Predictive Generative Networks. CoRR William Lotter, Gabriel Kreiman, David D. Cox
2014	A*	`conf`	Condition-invariant, top-down visual place recognition. ICRA Michael Milford, Walter J. Scheirer, Eleonora Vig, Arren Glover, Oliver Baumann, Jason B. Mattingley, David D. Cox
2014	A*	`conf`	Large-Scale Optimization of Hierarchical Features for Saliency Prediction in Natural Images. CVPR Eleonora Vig, Michael Dorr, David D. Cox
2014	J	`jnl`	Learning Person-Specific Representations From Faces in the Wild. IEEE Trans. Inf. Forensics Secur. Giovani Chiachia, Alexandre X. Falcão, Nicolas Pinto, Anderson Rocha, David D. Cox
2014	J	`jnl`	Perceptual Annotation: Measuring Human Vision to Improve Computer Vision. IEEE Trans. Pattern Anal. Mach. Intell. Walter J. Scheirer, Samuel E. Anthony, Ken Nakayama, David D. Cox
2014	J	`jnl`	Vision-based Simultaneous Localization and Mapping in Changing Outdoor Environments. J. Field Robotics Michael Milford, Eleonora Vig, Walter J. Scheirer, David D. Cox
2013	—	`conf`	Hyperopt: A Python Library for Optimizing the Hyperparameters of Machine Learning Algorithms. SciPy James Bergstra, Dan Yamins, David D. Cox
2013	J	`jnl`	Hyperparameter Optimization and Boosting for Classifying Facial Expressions: How good can a "Null" Model be? CoRR James Bergstra, David D. Cox
2013	—	`conf`	Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures. ICML (1) James Bergstra, Daniel Yamins, David D. Cox
2013	—	`conf`	SkData: Data Sets and Algorithm Evaluation Protocols in Python. SciPy James Bergstra, Nicolas Pinto, David D. Cox
2013	—	`conf`	The 2013 face recognition evaluation in mobile environment. ICB Manuel Günther, Artur Costa-Pazo, Changxing Ding, Elhocine Boutellaa, Giovani Chiachia, Honglei Zhang, Marcus A. Angeloni, Vitomir Struc, Elie Khoury, Esteban Vázquez-Fernández, Dacheng Tao, Messaoud Bengherabi, David D. Cox, Serkan Kiranyaz, Tiago de Freitas Pereira, Jerneja Zganec-Gros, Enrique Argones-Rúa, Nicolas Pinto, Moncef Gabbouj, Flávio Olmos Simões, Simon Dobrisek, Daniel González-Jiménez, Anderson Rocha, Mário Uliani Neto, Nikola Pavesic, Alexandre Xavier Falcão, Ricardo P. V. Violato, Sébastien Marcel
2012	J	`jnl`	High-throughput-derived biologically-inspired features for unconstrained face recognition. Image Vis. Comput. Nicolas Pinto, David D. Cox
2012	J	`jnl`	Making a Science of Model Search CoRR James Bergstra, Dan Yamins, David D. Cox
2012	A	`conf`	Person-Specific Subspace Analysis for Unconstrained Familiar Face Identification. BMVC Giovani Chiachia, Nicolas Pinto, William Robson Schwartz, Anderson Rocha, Alexandre X. Falcão, David D. Cox
2012	B	`conf`	Saliency-based selection of sparse descriptors for action recognition. ICIP Eleonora Vig, Michael Dorr, David D. Cox
2012	—	`conf`	Space-Variant Descriptor Sampling for Action Recognition Based on Saliency and Eye Movements. ECCV (7) Eleonora Vig, Michael Dorr, David D. Cox
2011	B	`conf`	Beyond simple features: A large-scale feature search approach to unconstrained face recognition. FG David D. Cox, Nicolas Pinto
2011	A	`conf`	Comparing state-of-the-art visual features on invariant object recognition tasks. WACV Nicolas Pinto, Youssef Barhomi, David D. Cox, James J. DiCarlo
2011	—	`conf`	Scaling up biologically-inspired computer vision: A case study in unconstrained face recognition on facebook. CVPR Workshops Nicolas Pinto, Zak Stone, Todd E. Zickler, David D. Cox
2010	—	`conf`	An Evaluation of the Invariance Properties of a Biologically-Inspired System for Unconstrained Face Recognition. BIONETICS Nicolas Pinto, David D. Cox
2010	—	`conf`	Towards an embedded biologically-inspired machine vision processor. FPT Vinay Sriram, David D. Cox, Kuen Hung Tsoi, Wayne Luk
2009	J	`jnl`	A High-Throughput Screening Approach to Discovering Good Forms of Biologically Inspired Visual Representation. PLoS Comput. Biol. Nicolas Pinto, David Doukhan, James J. DiCarlo, David D. Cox
2009	A*	`conf`	How far can you get with a modern face recognition test set using only simple features?. CVPR Nicolas Pinto, James J. DiCarlo, David D. Cox
2008	J	`jnl`	Why is Real-World Visual Object Recognition Hard? PLoS Comput. Biol. Nicolas Pinto, David D. Cox, James J. DiCarlo
2003	J	`jnl`	Functional magnetic resonance imaging (fMRI) "brain reading": detecting and classifying distributed patterns of fMRI activity in human visual cortex. NeuroImage David D. Cox, Robert L. Savoy