Tim Kaler

24 papers A* 1B 6Misc 1Journal 8Unranked 6
YearRankTypeTitle / Venue / Authors
2025 J jnl
Lessons Learned: A Multi-Agent Framework for Code LLMs to Learn and Improve.
CoRR
Yuanzhe Liu, Ryan Deng, Tim Kaler, Xuhao Chen, Charles E. Leiserson, Yao Ma, Jie Chen
2024 — conf
Speedcode: Software Performance Engineering Education via the Coding of Didactic Exercises.
IPDPS (Workshops)
Tim Kaler, Xuhao Chen, Brian Wheatman, Dorothy Curtis, Bruce Hoppe, Tao B. Schardl, Charles E. Leiserson
2024 J jnl
The Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Dataset.
CoRR
Claudio Bellei, Muhua Xu, Ross Phillips, Tom Robinson, Mark Weber, Tim Kaler, Charles E. Leiserson, Arvind, Jie Chen
2023 — conf
Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching.
MLSys
Tim Kaler, Alexandros-Stavros Iliopoulos, Philip Murzynowski, Tao B. Schardl, Charles E. Leiserson, Jie Chen
2023 J jnl
Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching.
CoRR
Tim Kaler, Alexandros-Stavros Iliopoulos, Philip Murzynowski, Tao B. Schardl, Charles E. Leiserson, Jie Chen
2022 — conf
Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining.
MLSys
Tim Kaler, Nickolas Stathas, Anne Ouyang, Alexandros-Stavros Iliopoulos, Tao B. Schardl, Charles E. Leiserson, Jie Chen
2022 — ch.
Executing Dynamic Data-Graph Computations Deterministically Using Chromatic Scheduling.
Massive Graph Analytics
Tim Kaler, William Hasenplaugh, Tao B. Schardl, Charles E. Leiserson
2022 — ch.
Ordering Heuristics for Parallel Graph Coloring.
Massive Graph Analytics
William Hasenplaugh, Tim Kaler, Tao B. Schardl, Charles E. Leiserson
2021 J jnl
Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining.
CoRR
Tim Kaler, Nickolas Stathas, Anne Ouyang, Alexandros-Stavros Iliopoulos, Tao B. Schardl, Charles E. Leiserson, Jie Chen
2021 — conf
PARAD: A Work-Efficient Parallel Algorithm for Reverse-Mode Automatic Differentiation.
APOCS
Tim Kaler, Tao B. Schardl, Brian Xie, Charles E. Leiserson, Jie Chen, Aldo Pareja, Georgios Kollias
2020 — conf
Cilkmem: Algorithms for Analyzing the Memory High-Water Mark of Fork-Join Parallel Programs.
APOCS
Tim Kaler, William Kuszmaul, Tao B. Schardl, Daniele Vettorel
2020 A* conf
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs.
AAAI
Aldo Pareja, Giacomo Domeniconi, Jie Chen, Tengfei Ma, Toyotaro Suzumura, Hiroki Kanezashi, Tim Kaler, Tao B. Schardl, Charles E. Leiserson
2020 — conf
High-Throughput Image Alignment for Connectomics using Frugal Snap Judgments.
HPEC
Tim Kaler, Brian Wheatman, Sarah Wooders
2019 J jnl
Cilkmem: Algorithms for Analyzing the Memory High-Water Mark of Fork-Join Parallel Programs.
CoRR
Tim Kaler, William Kuszmaul, Tao B. Schardl, Daniele Vettorel
2019 J jnl
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs.
CoRR
Aldo Pareja, Giacomo Domeniconi, Jie Chen, Tengfei Ma, Toyotaro Suzumura, Hiroki Kanezashi, Tim Kaler, Charles E. Leiserson
2019 B conf
High-throughput image alignment for connectomics using frugal snap judgments: poster.
PPoPP
Tim Kaler, Brian Wheatman, Sarah Wooders
2018 J jnl
Scalable Graph Learning for Anti-Money Laundering: A First Look.
CoRR
Mark Weber, Jie Chen, Toyotaro Suzumura, Aldo Pareja, Tengfei Ma, Hiroki Kanezashi, Tim Kaler, Charles E. Leiserson, Tao B. Schardl
2017 B conf
A Multicore Path to Connectomics-on-Demand.
PPoPP
Alexander Matveev, Yaron Meirovitch, Hayk Saribekyan, Wiktor Jakubiuk, Tim Kaler, Gergely Ódor, David M. Budden, Aleksandar Zlateski, Nir Shavit
2017 B conf
Optimal Reissue Policies for Reducing Tail Latency.
SPAA
Tim Kaler, Yuxiong He, Sameh Elnikety
2016 J jnl
Executing Dynamic Data-Graph Computations Deterministically Using Chromatic Scheduling.
ACM Trans. Parallel Comput.
Tim Kaler, William Hasenplaugh, Tao B. Schardl, Charles E. Leiserson
2015 B conf
Polylogarithmic Fully Retroactive Priority Queues via Hierarchical Checkpointing.
WADS
Erik D. Demaine, Tim Kaler, Quanquan C. Liu, Aaron Sidford, Adam Yedidia
2014 B conf
Executing dynamic data-graph computations deterministically using chromatic scheduling.
SPAA
Tim Kaler, William Hasenplaugh, Tao B. Schardl, Charles E. Leiserson
2014 B conf
Ordering heuristics for parallel graph coloring.
SPAA
William Hasenplaugh, Tim Kaler, Tao B. Schardl, Charles E. Leiserson
2010 Misc conf
Code in the air: simplifying sensing on smartphones.
SenSys
Tim Kaler, John Patrick Lynch, Timothy Peng, Lenin Ravindranath, Arvind Thiagarajan, Hari Balakrishnan, Samuel Madden