167 citations · 520 across the 43 of their papers we have counts for
6 papers · 1 filter
Neural Multisensory Scene Inference
Jae Hyun Lim, Pedro O. Pinheiro, Negar Rostamzadeh +2
For embodied agents to infer representations of the underlying 3D physical world they inhabit, they should efficiently combine multisensory cues from numerous trials, e.g., by look…
Instance Segmentation with Point Supervision
Issam H. Laradji, Negar Rostamzadeh, Pedro O. Pinheiro +2
Instance segmentation methods often require costly per-pixel labels. We propose a method that only requires point-level annotations. During training, the model only has access to a…
CLAREL: Classification via retrieval loss for zero-shot learning
Boris N. Oreshkin, Negar Rostamzadeh, Pedro O. Pinheiro +1
We address the problem of learning fine-grained cross-modal representations. We propose an instance-based deep metric learning approach in joint visual and textual space. The key n…
Reinforced Imitation in Heterogeneous Action Space
Konrad Zolna, Negar Rostamzadeh, Yoshua Bengio +2
Imitation learning is an effective alternative approach to learn a policy when the reward function is sparse. In this paper, we consider a challenging setting where an agent and an…
Towards Standardization of Data Licenses: The Montreal Data License
Misha Benjamin, Paul Gagnon, Negar Rostamzadeh +3
This paper provides a taxonomy for the licensing of data in the fields of artificial intelligence and machine learning. The paper's goal is to build towards a common framework for…
Adaptive Cross-Modal Few-Shot Learning
Chen Xing, Negar Rostamzadeh, Boris N. Oreshkin +1
Metric-based meta-learning techniques have successfully been applied to few-shot classification problems. In this paper, we propose to leverage cross-modal information to enhance m…