David D. Cox
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
30
Venues
17
Active years
2009–2024
Best venue rank
A*
Where they publish
Papers
30 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2024 | ACL | Self-Specialization: Uncovering Latent Expertise within Large Language Models. | Junmo Kang, Hongyin Luo, Yada Zhu, Jacob A. Hansen, James R. Glass, David D. Cox, Alan Ritter, Rogrio Feris, Leonid Karlinsky |
| 2023 | ASRU | Audio-Visual Neural Syntax Acquisition. | 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 | CVPR | ConStruct-VL: Data-Free Continual Structured VL Concepts Learning. | James Seale Smith, Paola Cascante-Bonilla, Assaf Arbelle, Donghyun Kim, Rameswar Panda, David D. Cox, Diyi Yang, Zsolt Kira, Rogrio Feris, Leonid Karlinsky |
| 2022 | AAAI | An Adversarial Framework for Generating Unseen Images by Activation Maximization. | Yang Zhang, Wang Zhou, Gaoyuan Zhang, David D. Cox, Shiyu Chang |
| 2022 | CVPR | VALHALLA: Visual Hallucination for Machine Translation. | Yi Li, Rameswar Panda, Yoon Kim, Chun-Fu Richard Chen, Rogrio Feris, David D. Cox, Nuno Vasconcelos |
| 2022 | ICASSP | On the Interplay between Sparsity, Naturalness, Intelligibility, and Prosody in Speech Synthesis. | 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 | ICML | ContentVec: An Improved Self-Supervised Speech Representation by Disentangling Speakers. | Kaizhi Qian, Yang Zhang, Heting Gao, Junrui Ni, Cheng-I Lai, David D. Cox, Mark Hasegawa-Johnson, Shiyu Chang |
| 2021 | ICML | Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators. | Yonggan Fu, Yongan Zhang, Yang Zhang, David D. Cox, Yingyan Lin |
| 2021 | ICML | Global Prosody Style Transfer Without Text Transcriptions. | Kaizhi Qian, Yang Zhang, Shiyu Chang, Jinjun Xiong, Chuang Gan, David D. Cox, Mark Hasegawa-Johnson |
| 2021 | WACV | Joint Visual-Temporal Embedding for Unsupervised Learning of Actions in Untrimmed Sequences. | Rosaura G. VidalMata, Walter J. Scheirer, Anna Kukleva, David D. Cox, Hilde Kuehne |
| 2020 | ICML | Unsupervised Speech Decomposition via Triple Information Bottleneck. | Kaizhi Qian, Yang Zhang, Shiyu Chang, Mark Hasegawa-Johnson, David D. Cox |
| 2019 | ICCV | Self-Supervised Moving Vehicle Tracking With Stereo Sound. | Chuang Gan, Hang Zhao, Peihao Chen, David D. Cox, Antonio Torralba |
| 2019 | PLDI | Triton: an intermediate language and compiler for tiled neural network computations. | Philippe Tillet, Hsiang-Tsung Kung, David D. Cox |
| 2018 | ICLR | On the Information Bottleneck Theory of Deep Learning. | Andrew M. Saxe, Yamini Bansal, Joel Dapello, Madhu Advani, Artemy Kolchinsky, Brendan D. Tracey, David D. Cox |
| 2018 | MICCAI | Conditional Infilling GANs for Data Augmentation in Mammogram Classification. | Eric Wu, Kevin Wu, David D. Cox, William Lotter |
| 2017 | ICASSP | Infomax-ICA using Hessian-free optimization. | Philippe Tillet, H. T. Kung, David D. Cox |
| 2017 | ICLR | Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning. | William Lotter, Gabriel Kreiman, David D. Cox |
| 2017 | MICCAI | A Multi-scale CNN and Curriculum Learning Strategy for Mammogram Classification. | William Lotter, Greg Sorensen, David D. Cox |
| 2017 | SC | Input-aware auto-tuning of compute-bound HPC kernels. | Philippe Tillet, David D. Cox |
| 2015 | CIARP | Improving Optimum-Path Forest Classification Using Confidence Measures. | Silas Evandro Nachif Fernandes, Walter J. Scheirer, David D. Cox, Joo Paulo Papa |
| 2015 | CIARP | Fine-Tuning Convolutional Neural Networks Using Harmony Search. | Gustavo H. Rosa, Joo Paulo Papa, Aparecido Nilceu Marana, Walter J. Scheirer, David D. Cox |
| 2014 | CVPR | Large-Scale Optimization of Hierarchical Features for Saliency Prediction in Natural Images. | Eleonora Vig, Michael Dorr, David D. Cox |
| 2014 | ICRA | Condition-invariant, top-down visual place recognition. | Michael Milford, Walter J. Scheirer, Eleonora Vig, Arren Glover, Oliver Baumann, Jason B. Mattingley, David D. Cox |
| 2013 | ICML | Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures. | James Bergstra, Daniel Yamins, David D. Cox |
| 2012 | BMVC | Person-Specific Subspace Analysis for Unconstrained Familiar Face Identification. | Giovani Chiachia, Nicolas Pinto, William Robson Schwartz, Anderson Rocha, Alexandre X. Falco, David D. Cox |
| 2012 | ECCV | Space-Variant Descriptor Sampling for Action Recognition Based on Saliency and Eye Movements. | Eleonora Vig, Michael Dorr, David D. Cox |
| 2012 | ICIP | Saliency-based selection of sparse descriptors for action recognition. | Eleonora Vig, Michael Dorr, David D. Cox |
| 2011 | CVPR | Scaling up biologically-inspired computer vision: A case study in unconstrained face recognition on facebook. | Nicolas Pinto, Zak Stone, Todd E. Zickler, David D. Cox |
| 2011 | WACV | Comparing state-of-the-art visual features on invariant object recognition tasks. | Nicolas Pinto, Youssef Barhomi, David D. Cox, James J. DiCarlo |
| 2009 | CVPR | How far can you get with a modern face recognition test set using only simple features?. | Nicolas Pinto, James J. DiCarlo, David D. Cox |