7 citations · 21 across the 12 of their papers we have counts for
14 papers
BLInD: Learning Driver Intent as a Distribution over Future Ego Trajectories
Flavian Pegado, Ronit Hire, Shreyas Rajesh +1
We present BLInD (Blind Learned Intent Distribution), a compact network that maps recent vehicle-state history (e.g. speed, curvature, indicator, and vehicle type) to a top-k distr…
AI For Global Climate Cooperation 2023 Competition Proceedings
Yoshua Bengio, Prateek Gupta, Lu Li +6
The international community must collaborate to mitigate climate change and sustain economic growth. However, collaboration is hard to achieve, partly because no global authority c…
MERMAIDE: Learning to Align Learners using Model-Based Meta-Learning
Arundhati Banerjee, Soham Phade, Stefano Ermon +1
We study how a principal can efficiently and effectively intervene on the rewards of a previously unseen learning agent in order to induce desirable outcomes. This is relevant to m…
Interactive Learning with Pricing for Optimal and Stable Allocations in Markets
Yigit Efe Erginbas, Soham Phade, Kannan Ramchandran
Large-scale online recommendation systems must facilitate the allocation of a limited number of items among competing users while learning their preferences from user feedback. As…
AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N
Tianyu Zhang, Andrew Williams, Soham Phade +5
Comprehensive global cooperation is essential to limit global temperature increases while continuing economic development, e.g., reducing severe inequality or achieving long-term e…
Interactive Recommendations for Optimal Allocations in Markets with Constraints
Yigit Efe Erginbas, Soham Phade, Kannan Ramchandran
Recommendation systems when employed in markets play a dual role: they assist users in selecting their most desired items from a large pool and they help in allocating a limited nu…