ashibaga
  • Site
      • Metric Learning
        • Musgrave ECCV’20 A Metric Learning Reality Check
        • Song CVPR’16 Deep Metric Learning via Lifted Structured Feature Embedding
        • Wang CVPR19 Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning
        • Wang CVPR’20 Cross-Batch Memory for Embedding Learning
        • Movshovitz ICCV’17 No fuss distance metric learning using proxies
        • Kim CVPR’20 Proxy Anchor Loss for Deep Metric Learning
        • Roth ICML’21 Simultaneous Similarity-based Self-Distillation for Deep Metric Learning
        • Radford ICML’21 CLIP (Learning Transferable Visual Models From Natural Language Supervision)
        • Roth CVPR’22 Integrating Language Guidance into Vision-based Deep Metric Learning
      • Learning from Noisy Labels
        • Northcutt ICML’20 Confident Learning: Estimating Uncertainty in Dataset Labels
        • Northcutt NeurIPS’21 Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks
      • Self Supervised Learning (SSL)
        • Chen ICML’20 SimCLR (A Simple Framework for Contrastive Learning of Visual Representations)
        • Grill NIPS’20 BYOL (Bootstrap Your Own Latent A New Approach to Self-Supervised Learning)
        • Chen CVPR’21 SimSiam (Exploring Simple Siamese Representation Learning)
        • Does ICLR’22 How Does SimSiam Avoid Collapse Without Negative Samples?
      • Representation Learning
        • Wang ICML’20 Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere
      • Other
        • Kudo EMNLP’18 SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing
        • Teja ICML’20 Optimizer Benchmarking Needs to Account for Hyperparameter Tuning
        • Zhao (KDD’23) Breaking the Curse of Quality Saturation with User-Centric Ranking
        • Xie (KDD’23) QUERT: Continual Pre-training of Language Model for Query Understanding in Travel Domain Search
        • Tensorflow Serving
        • 検索システム 実務者のための開発改善ガイドブック 11章 検索を成功させるための支援
      • Proceedings
        • SIGIR’23 ABSTRACT
        • SIGIR’22 ABSTRACT
        • SIGIR’21 ABSTRACT
        • SIGIR’20 ABSTRACT
        • SIGIR’19 ABSTRACT
      • Learning to Rank
        • Zhen ICLR’21 Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees?
        • Zhuang SIGIR’20 Feature Transformation for Neural Ranking Models
        • Grover ICLR’19 Stochastic Optimization of Sorting Networks via Continuous Relaxations
        • Cuturi NeurIPS’19 Differentiable Ranks and Sorting using Optimal Transport
        • Blondel ICML’20 Fast Differentiable Sorting and Ranking
        • Petersen ICML’21 Differentiable Sorting Networks for Scalable Sorting and Ranking Supervision
        • Petersen ICLR’22 Monotonic Differentiable Sorting Networks
        • Algorithm
        • Metric
  • Page
      • Other
        • Papers
        • Memo
  • « Wang ICML’20 ...
  • Kudo EMNLP’18... »
  • Other
    • Papers
    • Memo
  • « Wang ICML’20 ...
  • Kudo EMNLP’18... »
  • Source

    Other¶

    Papers¶

    • Kudo EMNLP’18 SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing
    • Teja ICML’20 Optimizer Benchmarking Needs to Account for Hyperparameter Tuning
    • Zhao (KDD’23) Breaking the Curse of Quality Saturation with User-Centric Ranking
    • Xie (KDD’23) QUERT: Continual Pre-training of Language Model for Query Understanding in Travel Domain Search

    Memo¶

    • Tensorflow Serving
    • 検索システム 実務者のための開発改善ガイドブック 11章 検索を成功させるための支援

    Back to top

    Created using Sphinx 8.2.3.