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Exploration in reinforcement learning (RL) remains an open challenge. RL algorithms rely on observing rewards to train the agent, and if informative rewards are sparse the agent learns slowly or may not learn at all. To improve exploration…

Machine Learning · Computer Science 2024-11-12 Simone Parisi , Alireza Kazemipour , Michael Bowling

Bitcoin-NG, a scalable blockchain protocol, divides each block into a key block and many micro blocks to effectively improve the transaction processing capacity. Bitcoin-NG has a special incentive mechanism (i.e. splitting transaction fees…

Cryptography and Security · Computer Science 2020-06-23 Taotao Wang , Xiaoqian Bai , Hao Wang , Soung Chang Liew , Shengli Zhang

Bandit-style algorithms have been studied extensively in stochastic and adversarial settings. Such algorithms have been shown to be useful in multiplayer settings, e.g. to solve the wireless network selection problem, which can be…

Networking and Internet Architecture · Computer Science 2019-04-30 Shunhao Oh , Anuja Meetoo Appavoo , Seth Gilbert

Direct preference optimization (\texttt{DPO}) has emerged as a promising approach for solving the alignment problem in AI. In this paper, we make two counter-intuitive observations about \texttt{DPO}. First, we show that \texttt{DPO} loss…

Learning control policies for complex, long-horizon tasks is a central challenge in robotics and autonomous systems. Signal Temporal Logic (STL) offers a powerful and expressive language for specifying such tasks, but its non-Markovian…

Robotics · Computer Science 2025-10-02 Yue Meng , Fei Chen , Chuchu Fan

An open distributed system can be secured by requiring participants to present proof of work and rewarding them for participation. The Bitcoin digital currency introduced this mechanism, which is adopted by almost all contemporary digital…

Cryptography and Security · Computer Science 2014-12-01 Ittay Eyal

Black box attacks, where adversaries have limited knowledge of the target model, pose a significant threat to machine learning systems. Adversarial examples generated with a substitute model often suffer from limited transferability to the…

Machine Learning · Computer Science 2024-10-22 Bar Avraham , Yisroel Mirsky

To understand the security threats to reinforcement learning (RL) algorithms, this paper studies poisoning attacks to manipulate \emph{any} order-optimal learning algorithm towards a targeted policy in episodic RL and examines the potential…

Machine Learning · Computer Science 2022-08-30 Anshuka Rangi , Haifeng Xu , Long Tran-Thanh , Massimo Franceschetti

WiFi densification leads to the existence of multiple overlapping coverage areas, which allows user stations (STAs) to choose between different Access Points (APs). The standard WiFi association method makes the STAs select the AP with the…

Networking and Internet Architecture · Computer Science 2019-03-04 Marc Carrascosa , Boris Bellalta

In the IEEE 802.11ax standard, a mode of operation called target wake time (TWT) is introduced towards enabling deterministic scheduling in WLAN networks. In the TWT mode, a group of stations (STAs) can negotiate with the access point (AP)…

Networking and Internet Architecture · Computer Science 2023-02-23 Rishabh Roy , Rajshekhar V Bhat , Preyas Hathi , Nadeem Akhtar , Naveen Mysore Balasubramanya

PAI Coin's Proof-of-Work (PoW) consensus mechanism utilizes the double SHA-256 hashing protocol-- the same mechanism used by Bitcoin Core. This compatibility with classic Bitcoin-style mining provides low barrier to entry for PAI Coin…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-22 Mark Harvilla , Jincheng Du

We study bandit algorithms under data poisoning attacks in a bounded reward setting. We consider a strong attacker model in which the attacker can observe both the selected actions and their corresponding rewards and can contaminate the…

Machine Learning · Computer Science 2022-05-05 Anshuka Rangi , Long Tran-Thanh , Haifeng Xu , Massimo Franceschetti

Reinforcement learning (RL) has shown extraordinary potential in aligning diffusion models to downstream tasks, yet most of them still suffer from significant reward hacking, which degrades generative diversity and quality by inducing…

Machine Learning · Computer Science 2026-05-14 Jiaming Li , Chenyu Zhu , Nanxi Yi , Youjun Bao , Li Sun , Quanying Lv , Xiang Fang , Daizong Liu , Jianjun Li , Kun He , Bowen Zhou , Zhiyuan Ma

Network slicing manages network resources as virtual resource blocks (RBs) for the 5G Radio Access Network (RAN). Each communication request comes with quality of experience (QoE) requirements such as throughput and latency/deadline, which…

Networking and Internet Architecture · Computer Science 2021-02-23 Yi Shi , Yalin E. Sagduyu

With much longer optimization time than that of untargeted attacks notwithstanding, the transferability of targeted attacks is still far from satisfactory. Recent studies reveal that fine-tuning an existing adversarial example (AE) in…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Hui Zeng , Sanshuai Cui , Biwei Chen , Anjie Peng

We study the adversarial bandit problem with composite anonymous delayed feedback. In this setting, losses of an action are split into $d$ components, spreading over consecutive rounds after the action is chosen. And in each round, the…

Machine Learning · Computer Science 2022-04-29 Zongqi Wan , Xiaoming Sun , Jialin Zhang

Modern action-conditioned video world models achieve strong short-horizon visual realism, yet remain unreliable on rare, interaction-critical transitions that dominate downstream planning and policy performance. Because passive…

An important feature of Proof-of-Work (PoW) blockchains is full dynamic availability, allowing miners to go online and offline while requiring only 50% of the online miners to be honest. Existing Proof-of-stake (PoS), Proof-of-Space and…

Cryptography and Security · Computer Science 2021-02-22 Soubhik Deb , Sreeram Kannan , David Tse

Weighting the p-values is a well-established strategy that improves the power of multiple testing procedures while dealing with heterogeneous data. However, how to achieve this task in an optimal way is rarely considered in the literature.…

Statistics Theory · Mathematics 2019-03-22 Guillermo Durand

We consider the subset selection problem for function $f$ with constraint bound $B$ that changes over time. Within the area of submodular optimization, various greedy approaches are commonly used. For dynamic environments we observe that…

Data Structures and Algorithms · Computer Science 2021-10-12 Vahid Roostapour , Aneta Neumann , Frank Neumann , Tobias Friedrich
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