LibAUC: A Deep Learning Library for X-Risk Optimization
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Updated
Jun 14, 2024 - Python
LibAUC: A Deep Learning Library for X-Risk Optimization
Critical difference diagram with Wilcoxon-Holm post-hoc analysis.
Tensorflow implementations of various Learning to Rank (LTR) algorithms.
rec_pangu is a flexible open-source project for recommendation systems. It incorporates diverse AI models like ranking algorithms, sequence recall, multi-interest models, and graph-based techniques. Designed for both beginners and advanced users, it enables rapid construction of efficient, custom recommendation engines.
👤 Multi-Armed Bandit Algorithms Library (MAB) 👮
Code and Data for the paper: "Learning to Ask Good Questions: Ranking Clarification Questions using Neural Expected Value of Perfect Information"
Document Search Engine Tool
siamese dssm sentence_similarity sentece_similarity_rank tensorflow
TensorFlow implementation of "Learning to Rank Question-Answer Pairs using Hierarchical Recurrent Encoder with Latent Topic Clustering," NAACL-18
A set of RL experiments. Currently including: (1) the MDP rank experiment, based on policy gradient algorithm
A personified chatbot responding to a query based on the answering pattern of Dr. APJ Abdul Kalam using Information Retrieval, Natural Language Processing, and Deep Learning techniques.
Potential energy ranking for domain generalization (DG)
Sklearn-ranking is ranking algorithm used for recommendation system algorithm. RANKSVM, RANKBOOST, RANKNET is included in this package
Neural Response Ranker for Alana, Heriot-Watt University's Alexa Prize Socialbot
Building and evaluating a ranking model using the MSLR-WEB10K dataset
A Python 3.12 implementation of the Schulze method for ranking candidates.
A bridge finder for the card 'Small World' in the card game 'Yu-Gi-Oh!'.
Extractive summarizationof medical transcriptions
Tiny Ranking Engine, that do searching in unlimited number of files in directory called data and calculate Terms weighting.
LTR with gradient boosting
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