176 citations · 826 across the 63 of their papers we have counts for
9 papers · 1 filter
A Berkeley View of Systems Challenges for AI
Ion Stoica, Dawn Song, Raluca Ada Popa +11
With the increasing commoditization of computer vision, speech recognition and machine translation systems and the widespread deployment of learning-based back-end technologies suc…
Disentangling Dynamics and Content for Control and Planning
Ershad Banijamali, Ahmad Khajenezhad, Ali Ghodsi +1
In this paper, We study the problem of learning a controllable representation for high-dimensional observations of dynamical systems. Specifically, we consider a situation where th…
JADE: Joint Autoencoders for Dis-Entanglement
Ershad Banijamali, Amir-Hossein Karimi, Alexander Wong +1
The problem of feature disentanglement has been explored in the literature, for the purpose of image and video processing and text analysis. State-of-the-art methods for disentangl…
Improving the Accuracy of Pre-trained Word Embeddings for Sentiment Analysis
Seyed Mahdi Rezaeinia, Ali Ghodsi, Rouhollah Rahmani
Sentiment analysis is one of the well-known tasks and fast growing research areas in natural language processing (NLP) and text classifications. This technique has become an essent…
Robust Locally-Linear Controllable Embedding
Ershad Banijamali, Rui Shu, Mohammad Ghavamzadeh +2
Embed-to-control (E2C) is a model for solving high-dimensional optimal control problems by combining variational auto-encoders with locally-optimal controllers. However, the E2C mo…
Deep Structure for end-to-end inverse rendering
Shima Kamyab, Ali Ghodsi, S. Zohreh Azimifar
Inverse rendering in a 3D format denoted to recovering the 3D properties of a scene given 2D input image(s) and is typically done using 3D Morphable Model (3DMM) based methods from…