Mark Sandler
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
21
Venues
12
Active years
2004–2025
Best venue rank
A*
Where they publish
Papers
21 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | How new data permeates LLM knowledge and how to dilute it. | Chen Sun, Renat Aksitov, Andrey Zhmoginov, Nolan Andrew Miller, Max Vladymyrov, Ulrich Rueckert, Been Kim, Mark Sandler |
| 2023 | CVPR | Decentralized Learning with Multi-Headed Distillation. | Andrey Zhmoginov, Mark Sandler, Nolan Miller, Gus Kristiansen, Max Vladymyrov |
| 2022 | CVPR | Fine-tuning Image Transformers using Learnable Memory. | Mark Sandler, Andrey Zhmoginov, Max Vladymyrov, Andrew Jackson |
| 2022 | ICML | HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning. | Andrey Zhmoginov, Mark Sandler, Maksym Vladymyrov |
| 2021 | ICML | Meta-Learning Bidirectional Update Rules. | Mark Sandler, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Tom Madams, Andrew Jackson, Blaise Agera y Arcas |
| 2020 | ACCV | SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection. | Keren Ye, Adriana Kovashka, Mark Sandler, Menglong Zhu, Andrew G. Howard, Marco Fornoni |
| 2020 | CVPR | Structured Multi-Hashing for Model Compression. | Elad Eban, Yair Movshovitz-Attias, Hao Wu, Mark Sandler, Andrew Poon, Yerlan Idelbayev, Miguel . Carreira-Perpin |
| 2020 | ECCV | SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection. | Keren Ye, Adriana Kovashka, Mark Sandler, Menglong Zhu, Andrew G. Howard, Marco Fornoni |
| 2019 | CVPR | MnasNet: Platform-Aware Neural Architecture Search for Mobile. | Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Mark Sandler, Andrew Howard, Quoc V. Le |
| 2019 | ICCV | Searching for MobileNetV3. | Andrew Howard, Ruoming Pang, Hartwig Adam, Quoc V. Le, Mark Sandler, Bo Chen, Weijun Wang, Liang-Chieh Chen, Mingxing Tan, Grace Chu, Vijay Vasudevan, Yukun Zhu |
| 2019 | ICLR | K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning. | Pramod Kaushik Mudrakarta, Mark Sandler, Andrey Zhmoginov, Andrew G. Howard |
| 2018 | CVPR | MobileNetV2: Inverted Residuals and Linear Bottlenecks. | Mark Sandler, Andrew G. Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen |
| 2018 | ECCV | NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications. | Tien-Ju Yang, Andrew G. Howard, Bo Chen, Xiao Zhang, Alec Go, Mark Sandler, Vivienne Sze, Hartwig Adam |
| 2013 | WWW | Understanding latency variations of black box services. | Darja Krushevskaja, Mark Sandler |
| 2010 | WWW | Monitoring algorithms for negative feedback systems. | Mark Sandler, S. Muthukrishnan |
| 2007 | KDD | Hierarchical mixture models: a probabilistic analysis. | Mark Sandler |
| 2006 | PODS | Privacy via pseudorandom sketches. | Nina Mishra, Mark Sandler |
| 2005 | FOCS | On Learning Mixtures of Heavy-Tailed Distributions. | Anirban Dasgupta, John E. Hopcroft, Jon M. Kleinberg, Mark Sandler |
| 2005 | KDD | On the use of linear programming for unsupervised text classification. | Mark Sandler |
| 2004 | SODA | Network failure detection and graph connectivity. | Jon M. Kleinberg, Mark Sandler, Aleksandrs Slivkins |
| 2004 | STOC | Using mixture models for collaborative filtering. | Jon M. Kleinberg, Mark Sandler |