Trotman, A., Mackenzie, J., Parameswaran, P., & Lin, J. (2022). A Common Framework for Exploring Document-at-a-Time and Score-at-a-Time Retrieval Methods Presented at the A Common Framework for Exploring Document-at-a-Time and Score-at-a-Time Retrieval Methods conference. https://doi.org/10.1145/3477495.3531657
References
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Zhong, Y., Xiao, J., Vetterli, T., Matin, M., Loo, E., Lin, J., … Shapira, O. (2022). Improving Precancerous Case Characterization via Transformer-Based Ensemble Learning Presented at the Improving Precancerous Case Characterization via Transformer-Based Ensemble Learning conference. Retrieved from https://aclanthology.org/2022.emnlp-industry.38
Xin, J., Tang, R., Jiang, Z., Yu, Y., & Lin, J. (2022). Building an Efficiency Pipeline: Commutativity and Cumulativeness Of Efficiency Operators for Transformers ArXiv, abs/2208.00483. https://doi.org/10.48550/arXiv.2208.00483
Li, M., Zhang, X., Xin, J., Zhang, H., & Lin, J. (2022). Certified Error Control of Candidate Set Pruning for Two-Stage Relevance Ranking Presented at the Certified Error Control of Candidate Set Pruning for Two-Stage Relevance Ranking conference. Retrieved from https://aclanthology.org/2022.emnlp-main.23
Jiang, Z., Dai, Y., Xin, J., Li, M., & Lin, J. (2022). Few-Shot Non-Parametric Learning With Deep Latent Variable Model ArXiv, abs/2206.11573. https://doi.org/10.48550/arXiv.2206.11573
Ilyas, I., & Naumann, F. (2022). Data Errors: Symptoms, Causes and Origins IEEE Data Engineering Bulletin, 45, 4-9. Retrieved from http://sites.computer.org/debull/A22mar/p4.pdf
Guo, R., Guo, V., Kim, A., Hildred, J., & Daudjee, K. (2022). Hydrozoa: Dynamic Hybrid-Parallel DNN Training on Serverless Containers Presented at the Hydrozoa: Dynamic Hybrid-Parallel DNN Training on Serverless Containers conference. Retrieved from https://proceedings.mlsys.org/paper/2022/hash/ea5d2f1c4608232e07d3aa3d998e5135-Abstract.html
Craswell, N., Mitra, B., Yilmaz, E., Campos, D., Lin, J., Voorhees, E. M., & Soboroff, I. (2022). Overview of the TREC 2022 Deep Learning Track Presented at the Overview of the TREC 2022 Deep Learning Track conference. Retrieved from https://trec.nist.gov/pubs/trec31/papers/Overview_deep.pdf
Arabzadeh, N., Seifikar, M., & Clarke, C. (2022). Unsupervised Question Clarity Prediction Through Retrieved Item Coherency Presented at the Unsupervised Question Clarity Prediction Through Retrieved Item Coherency conference. https://doi.org/10.1145/3511808.3557719
Durvasula, S., Kiguru, R., Mathur, S., Xu, J., Lin, J., & Vijaykumar, N. (2022). VoxelCache: Accelerating Online Mapping in Robotics and 3D Reconstruction Tasks ArXiv, abs/2210.08729. https://doi.org/10.48550/arXiv.2210.08729