Now showing items 5-10 of 10

    • Representations That Learn vs. Learning Representations 

      Liao, Qianli; Poggio, Tomaso (2018-12-31)
      During the last decade, we have witnessed tremendous progress in Machine Learning and especially the area of Deep Learning, a.k.a. “Learning Representations” (LearnRep for short). There is even an International Conference ...
    • Spatial IQ Test for AI 

      Hilton, Erwin; Liao, Qianli; Poggio, Tomaso (2017-12-31)
      We introduce SITD (Spatial IQ Test Dataset), a dataset used to evaluate the capabilities of computational models for pattern recognition and visual reasoning. SITD is a generator of images in the style of the Raven Progressive ...
    • Technical Report: Building a Neural Ensemble Decoder by Extracting Features Shared Across Multiple Populations 

      Chang, Chia-Jung (2019-09-05)
      To understand whether and how a certain population of neurons represent behavioral-relevant vari- ables, building a neural ensemble decoder has been used to extract information from the recorded activity. Among different ...
    • Universal Format Conversions 

      Liao, Qianli (2020-06-05)
      Information is the fuel for intelligence. Any competitive intelligence system should be information hungry. “Formats” on the other hand, is the container for information. Accessing information without the ability to decipher ...
    • Universal Metaphysics 

      Liao, Qianli (2019-12-31)
      The development of natural science especially physics allows us to understand to a large extent the material world. However, the world also contains a large amount of concepts that are non-material and abstract, which are ...
    • When Is Handcrafting Not a Curse? 

      Liao, Qianli; Poggio, Tomaso (2018-12-31)
      Recently, with the proliferation of deep learning, there is a strong trend of abandoning handcrafted sys- tems/features in machine learning and AI by replacing them with “end-to-end” systems “learned from scratch”. These ...