Speaker "Sen Zhao" Details Back



Unleashing the power of monotonicity with TensorFlow Lattice


The key to machine learning is getting the right flexibility. For many ML problems, we have prior knowledge about global trends the model should be capturing, like that predicted travel time should go up if traffic gets worse. But flexible models like DNN's and RF's can have a hard time capturing such global trends given noisy training data, which limits their ability to extrapolate well when you run a model on examples different than your training data. TensorFlow's new TensorFlow Lattice tools let you create flexible models that can respect the global trends you request, producing easier-to-debug models that generalize well. TF Lattice provides new TF Estimators that make capturing your global trends easy, and we'll also explain the underlying new TF Lattice operators that you can use to create your own deeper lattice networks.


Sen Zhao is a statistician at Google AI. Zhao's R&D work focuses on designing and developing controllable and interpretative machine learning algorithms that solve Google product needs. Zhao obtained his PhD degree from the University of Washington and BA from Carleton College.