Publications
- Accelerating training and inference of graph neural networks with fast sampling and pipeliningTim Kaler, Nickolas Stathas, Anne Ouyang, Alexandros-Stavros Iliopoulos, Tao Schardl, Charles E. Leiserson & Jie Chen. 2022. Accelerating training and inference of graph neural networks with fast sampling and pipelining. Proceedings of Machine Learning and Systems 4. 172–189.
- PARAD: A Work-Efficient Parallel Algorithm for Reverse-Mode Automatic DifferentiationTim Kaler, Tao B. Schardl, Brian Xie, Charles E. Leiserson, Jie Chen, Aldo Pareja & Georgios Kollias. 2021. PARAD: A Work-Efficient Parallel Algorithm for Reverse-Mode Automatic Differentiation. In Symposium on Algorithmic Principles of Computer Systems, SIAM.
- Evolvegcn: Evolving graph convolutional networks for dynamic graphsAldo Pareja, Giacomo Domeniconi, Jie Chen, Tengfei Ma, Toyotaro Suzumura, Hiroki Kanezashi, … Charles Leiserson. 2020. Evolvegcn: Evolving graph convolutional networks for dynamic graphs. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 34, 5363–5370.
- High-Throughput Image Alignment for Connectomics using Frugal Snap Judgments Best student paperTim Kaler, Brian Wheatman & Sarah Wooders. 2020. High-Throughput Image Alignment for Connectomics using Frugal Snap Judgments. In 2020 IEEE High Performance Extreme Computing Conference (HPEC), IEEE.
- Cilkmem: Algorithms for analyzing the memory high-water mark of fork-join parallel programs Best paper finalistTim Kaler, William Kuszmaul, Tao B. Schardl & Daniele Vettorel. 2020. Cilkmem: Algorithms for analyzing the memory high-water mark of fork-join parallel programs. In Symposium on Algorithmic Principles of Computer Systems, 162–176. SIAM.
- High-throughput image alignment for connectomics using frugal snap judgments: posterTim Kaler, Brian Wheatman & Sarah Wooders. 2019. High-throughput image alignment for connectomics using frugal snap judgments: poster. In Proceedings of the 24th Symposium on Principles and Practice of Parallel Programming, 433–434. ACM.
- Scalable Graph Learning for Anti-Money Laundering: A First LookMark Weber, Jie Chen, Toyotaro Suzumura, Aldo Pareja, Tengfei Ma, Hiroki Kanezashi, … Tao B. Schardl. 2018. Scalable Graph Learning for Anti-Money Laundering: A First Look. ArXiv Preprint ArXiv:1812.00076.
- A multicore path to connectomics-on-demand Best paper finalistAlexander Matveev, Yaron Meirovitch, Hayk Saribekyan, Wiktor Jakubiuk, Tim Kaler, Gergely Odor, … Nir Shavit. 2017. A multicore path to connectomics-on-demand. In Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 267–281. ACM.
- Optimal Reissue Policies for Reducing Tail LatencyTim Kaler, Yuxiong He & Sameh Elnikety. 2017. Optimal Reissue Policies for Reducing Tail Latency. In Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures, 195–206. ACM.
- Executing dynamic data-graph computations deterministically using chromatic schedulingTim Kaler, William Hasenplaugh, Tao B. Schardl & Charles E. Leiserson. 2016. Executing dynamic data-graph computations deterministically using chromatic scheduling. ACM Transactions on Parallel Computing (TOPC) 3(1). 2.
- Polylogarithmic Fully Retroactive Priority Queues via Hierarchical CheckpointingErik D. Demaine, Tim Kaler, Quanquan Liu, Aaron Sidford & Adam Yedidia. 2015. Polylogarithmic Fully Retroactive Priority Queues via Hierarchical Checkpointing. In Workshop on Algorithms and Data Structures, 263–275. Springer.
- Ordering heuristics for parallel graph coloringWilliam Hasenplaugh, Tim Kaler, Tao B. Schardl & Charles E. Leiserson. 2014. Ordering heuristics for parallel graph coloring. In Proceedings of the 26th ACM symposium on Parallelism in algorithms and architectures, 166–177. ACM.
- Executing dynamic data-graph computations deterministically using chromatic schedulingTim Kaler, William Hasenplaugh, Tao B. Schardl & Charles E. Leiserson. 2014. Executing dynamic data-graph computations deterministically using chromatic scheduling. In Proceedings of the 26th ACM symposium on Parallelism in algorithms and architectures, 154–165. ACM.
- Chromatic scheduling of dynamic data-graph computationsTim Kaler. 2013. Chromatic scheduling of dynamic data-graph computations. Massachusetts Institute of Technology dissertation.
- Spatial Data Structures-Performance ComparisionTim Kaler & Oscar Moll. 2012. Spatial Data Structures-Performance Comparision. O. Moll (Ed.).
- Code in the air: simplifying sensing on smartphonesTim Kaler, John Patrick Lynch, Timothy Peng, Lenin Ravindranath, Arvind Thiagarajan, Hari Balakrishnan & Sam Madden. 2010. Code in the air: simplifying sensing on smartphones. In Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems, 407–408. ACM.
- Cache Efficient Bloom Filters for Shared Memory MachinesTim Kaler. Cache Efficient Bloom Filters for Shared Memory Machines.
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