Instruct: Given the title of a scientific paper, retrieve paper titles that are cited by the given paper.
Query: Xavier : A Reinforcement-Learning Approach to TCP Congestion Control CS 221 Final Report
TCP ex machina: computer-generated congestion control
Virtual clock: a new traffic control algorithm for packet switching networks
A unified framework for frequency control and congestion management
Congestion Avoidance with Incremental Filter Aggregation in Content-Based Routing Networks
Adaptive call admission control under quality of service constraints: a reinforcement learning solution
CoCoA+: an advanced congestion control mechanism for CoAP
Advanced IEEE 802.11ax TCP aware scheduling under unreliable channels
V2X Application-Reliability Analysis of Data-Rate and Message-Rate Congestion Control Algorithms
A distributed reinforcement learning scheme for network routing
Dynamic TXOP HCCA reclaiming scheduler with transmission time estimation for IEEE 802.11e real-time networks
Cross-layer cooperation to boost multipath TCP performance in cloud networks
Congestion control mechanism for Internet-of-Things (IOT) paradigm
Congestion Management Using Multiobjective Particle Swarm Optimization
Improving TCP performance in mobile computing environments
Analysis of DCTCP: stability, convergence, and fairness
Framework for Traffic Congestion Management
Reinforcement learning of traffic light controllers adapting to traffic congestion
Traffic-aware congestion control (TACC) for wireless multimedia sensor networks
Approximate fair bandwidth allocation: A method for simple and flexible traffic management
An application-level solution for the TCP-incast problem in data center networks
A Low Voltage Four-Quadrant Analog Multiplier Using Triode-MOSFETs
Simple statistical gradient-following algorithms for connectionist reinforcement learning
An inductorless wideband balun-LNA in 65nm CMOS with balanced output
Statistical transformer networks: learning shape and appearance models via self supervision
tensor completion and lown - rank tensor recovery via convex optimization .