Papers I Read Notes and Summaries

Hierarchical RL Using an Ensemble of Proprioceptive Periodic Policies

Introduction

  • The paper proposes a simple and robust approach for hierarchically training an agent in the sparse... Continue reading


Efficient Lifelong Learning with A-GEM

Contributions

  • A new (and more realistic) evaluation protocol for lifelong learning where each data point is observed... Continue reading


Pre-training Graph Neural Networks with Kernels

Introduction

  • The paper proposes a pretraining technique that can be used with the GNN architecture for... Continue reading


Smooth Loss Functions for Deep Top-k Classification

Introduction

  • For top-k classification tasks, cross entropy is widely used as the learning objective even though it... Continue reading


Hindsight Experience Replay

Introduction

  • Hindsight Experience Replay(HER) is a sample efficient technique to learn from sparse rewards.

  • Continue reading


Representation Tradeoffs for Hyperbolic Embeddings

Introduction

  • The paper describes a combinatorial approach to embed trees into hyperbolic spaces without performing optimization.

  • ... Continue reading

Learned Optimizers that Scale and Generalize

Introduction

  • The paper introduces a learned gradient descent optimizer that has low memory and computational overhead and... Continue reading


One-shot Learning with Memory-Augmented Neural Networks

Introduction

  • The paper demonstrates that Memory Augmented Neural Networks (MANN) are suitable for one-shot learning by introducing... Continue reading


BabyAI - First Steps Towards Grounded Language Learning With a Human In the Loop

Introduction

  • BabyAI is a research platform to investigate and support the feasibility of including humans in the... Continue reading


Poincaré Embeddings for Learning Hierarchical Representations

Introduction

  • Much of the work in representation leaning uses Euclidean vector spaces to embed datapoints (like words,... Continue reading